Young-Jun Son

Interests

Teaching

Discrete Event Simulation, Computer Integrated Manufacturing, Distributed Multi-paradigm Simulation Systems, Integrated Manufacturing Systems

Research

Agent-based Simulation, Distributed Simulation, Human Decision Making (Applications in Emergency Evacuation and Transportation), Computer Integrated Manufacturing, Simulation-based Planning and Control, UAV/UGV Coordination

Courses

Scholarly Contributions

Books

• Kugler, T., Smith, J. C., Son, Y., & Connolly, T. (2008). Decision modeling and behavior in uncertain and complex environments. Springer.

Journals/Publications

• Lee, S., & Son, Y. (2020). Extended decision field theory with social-learning for long-term decision-making processes in social networks. Information Sciences, 512, 1293-1307.
• Richards, J. P., Done, A. J., Barber, S. R., Jain, S., Son, Y., & Chang, E. H. (2020). Virtual coach: the next tool in functional endoscopic sinus surgery education. International Forum of Allergy & Rhinology, 10(1), 97-102.
• Jain, S., Lee, S., Barber, S. R., Chang, E. H., & Son, Y. (2019). Virtual reality based hybrid simulation for functional endoscopic sinus surgery. IISE Transactions on Healthcare Systems Engineering, 1-15.
• Lee, S., Jain, S., Yuan, Y., Zhang, Y., Yang, H., Liu, J., & Son, Y. (2019). Design and development of a DDDAMS-based border surveillance system via UVs and hybrid simulations. Expert Systems with Applications, 128, 109-123.
• Masoud, S., Chowdhury, B., Son, Y., Kubota, C., & Tronstad, R. (2019). Simulation based optimization of resource allocation and facility layout for vegetable grafting operations. Computers and Electronics in Agriculture, 163, 104845.
• Shin, M., Lee, H., Ryu, K., Cho, Y., & Son, Y. (2019). A two-phased perishable inventory model for production planning in a food industry. Computers & Industrial Engineering, 133, 175-185.
• Barber, S. R., Jain, S., Son, Y., & Chang, E. H. (2018). Virtual Functional Endoscopic Sinus Surgery Simulation with 3D-Printed Models for Mixed-Reality Nasal Endoscopy. Otolaryngology–Head and Neck Surgery, 159(5), 933-937.
• Dolgui, A., Tiwari, M. K., Sinjana, Y., Kumar, S. K., & Son, Y. (2018). Optimising integrated inventory policy for perishable items in a multi-stage supply chain. International Journal of Production Research, 56(1-2), 902-925.
• Hu, B., Meng, C., Xu, D., & Son, Y. (2018). Supply chain coordination under vendor managed inventory-consignment stocking contracts with wholesale price constraint and fairness. International Journal of Production Economics, 202, 21-31.
• Masoud, S., Son, Y., Kubota, C., & Tronstad, R. E. (2018). Evaluation of simulation-based optimization in grafting labor allocation. Applied Engineering in Agriculture, 34, 479-489.
• Minaeian, S., Liu, J., & Son, Y. (2018). Effective and Efficient Detection of Moving Targets From a UAV’s Camera. IEEE Transactions on Intelligent Transportation Systems, 19(2), 497-506.
• Nageshwaraniyer, Y. (2018). A mine-to-mill economic analysis model and spectral imaging-based tracking system for a copper mine. Journal of the Southern African Institute of Mining and Metallurgy, 118, 7 - 14.
• Shin, M., Ryu, D., Han, J., Kim, K., & Son, Y. (2018). Preliminary design of a production automation framework for a pyroprocessing facility. Nuclear Engineering and Technology, 50(3), 478-487.
• Son, Y., Kim, K., & Sai, S. (2018). A Mine-To-Mill Economic Analysis Model and Spectral imaging-based tracking system for a copper mine. The Southern African Inistitute of Mining and Metallurgy (SAIMM), 118(1), 7-14.
• Tronstad, R. E., Kubota, C., Son, Y., & Masoud, S. (2018). Evaluation of simulation based optimization in grafting labor allocation. Applied Engineering in Agriculture, 34(3), 479-489.
• Kim, S., & Son, Y. (2017). Lane selection behavior modeling in an agent-based traffic simulation.
• Kim, S., Meng, C., & Son, Y. (2017). Simulation-based machine shop operations scheduling system for energy cost reduction. Simul. Model. Pract. Theory, 77, 68-83.
• Kim, S., Son, Y., Tian, Y., Chiu, Y., & Yang, C. D. (2017). Cognition-based hierarchical en route planning for multi-agent traffic simulation. Expert Systems with Applications, 85, 335-347.
• Kubota, C., Meng, C., Son, Y., Lewis, M., Spalholz, H., & Tronstad, R. (2017). Horticultural, systems-engineering and economic evaluations of short-term plant storage techniques as a labor management tool for vegetable grafting nurseries. PLOS ONE, 12(2), e0170614.
• Tronstad, R. E., Spalholz, H., Lewis, M., Son, Y., Meng, C., & Kubota, C. (2017). Horticultural, systems-engineering and economic evaluations of short-term plant storage techniques as a labor management tool for vegetable grafting nurseries. PLOS ONE, 12(2). doi:10.1371/journal.pone.0170614
• Xu, X., Ju, R., Liu, X., Li, G., & Son, Y. (2017). Extending HTN to planning and execution control for small combat unit simulation. International Journal of Modeling, Simulation, and Scientific Computing, 08(02), 1750032.
• Hu, B., Meng, C., Xu, D., & Son, Y. J. (2016). Three-echelon supply chain coordination with a loss-averse retailer and revenue sharing contracts. INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 179, 192-202.
• Kim, S., Son, Y., Chiu, Y., Jeffers, M., & Yang, C. D. (2016). Impact of road environment on drivers’ behaviors in dilemma zone: Application of agent-based simulation. Accident Analysis & Prevention, 96, 329-340.
• Minaeian, S., Liu, J., & Son, Y. (2016). Vision-Based Target Detection and Localization via a Team of Cooperative UAV and UGVs. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 46(7), 1005-1016.
• Qin, X., Lin, L., Lysecky, S., Roveda, J., Son, Y., & Sprinkle, J. (2016). A modular framework to enable rapid evaluation and exploration of energy management methods in smart home platforms. Energy Systems, 7(2), 215-235.
• Xu, D., Nageshwaraniyer, S. S., & Son, Y. (2016). A service-oriented simulation integration platform for hierarchical manufacturing planning and control. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 54(23), 7212-7230.
• Nageshwaraniyer, S. S., Kim, K., & Son, Y. (2015). Optimal blast design using a discrete event simulation model in a hard rock mine. SME mining magazine.
• Khaleghi, A. M., Xu, D., Minaeian, S., Li, M., Yuan, Y., Liu, J., Son, Y., Vo, C., & Lien, J. (2014). A DDDAMS-BASED UAV AND UGV TEAM FORMATION APPROACH FOR SURVEILLANCE AND CROWD CONTROL. PROCEEDINGS OF THE 2014 WINTER SIMULATION CONFERENCE (WSC), 2907-2918.
• Kubota, C. -., Lewis, M., Tronstad, R. E., & Son, Y. -. (2014). Scenario-based cost analysis for vegetable grafting nurseries of different technology and size. HortScience.
• Kucuksari, S., Khaleghi, A. M., Hamidi, M., Zhang, Y. e., Szidarovszky, F., Bayraksan, G., & Son, Y. (2014). An Integrated GIS, optimization and simulation framework for optimal PV size and location in campus area environments. APPLIED ENERGY, 113, 1601-1613.
• Kucuksari, S., Khaleghi, A. M., Hamidi, M., Zhang, Y., Szidarovszky, F., Bayraksan, G., & Son, Y. (2014). An Integrated GIS, optimization and simulation framework for optimal PV size and location in campus area environments. Applied Energy, 113, 1601-1613.
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  Abstract: Finding the optimal size and locations for Photovoltaic (PV) units has been a major challenge for distribution system planners and researchers. In this study, a framework is proposed to integrate Geographical Information Systems (GIS), mathematical optimization, and simulation modules to obtain the annual optimal placement and size of PV units for the next two decades in a campus area environment. First, a GIS module is developed to find the suitable rooftops and their panel capacity considering the amount of solar radiation, slope, elevation, and aspect. The optimization module is then used to maximize the long-term net profit of PV installations considering various costs of investment, inverter replacement, operation, and maintenance as well as savings from consuming less conventional energy. A voltage profile of the electricity distribution network is then investigated in the simulation module. In the case of voltage limit violation by intermittent PV generations or load fluctuations, two mitigation strategies, reallocation of the PV units or installation of a local storage unit, are suggested. The proposed framework has been implemented in a real campus area, and the results show that it can effectively be used for long-term installation planning of PV panels considering both the cost and power quality. © 2013 Elsevier Ltd.
• Meng, C., Dong, X. u., Son, Y., Kubota, C., Lewis, M., & Tronstad, R. (2014). An integrated simulation and AHP approach to vegetable grafting operation design. Computers and Electronics in Agriculture, 102, 73-84.
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  Abstract: For vegetable seedling propagators, integrating grafting technology into their propagation operations is critical to keeping or expanding market share in the near future. In this paper, an integrated discrete event simulation and Analytic Hierarchy Process (AHP) approach is proposed to help vegetable seedling propagators design grafting operation. The proposed approach consists of four steps: (1) defining performance criteria and factors (i.e. system alternative parameters and noise factors), (2) identifying significant factors via Design of Experiment (DOE), (3) evaluating system alternatives, and (4) AHP. For steps 2 and 3, a generic propagation simulator is developed with the focus on specific grafting operations (e.g. creating rootstocks, scions and grafted seedlings) while considering biological factors (e.g. seed disease and disease infection). Both classic and fuzzy AHP methods are adopted for addressing multiple criteria (e.g. variable cost, grafting throughput time, total capital expenses, resource utilization and percentage of order fulfilled in time with acceptable quality) of decisions. To address the imprecise ranking led by utilizing sample means of alternative performance data in pairwise comparison, a Best Alternative Search (BAS) procedure is proposed for AHP by considering bounds of confidence intervals in ranking alternatives. In the experiments, six system alternatives involving three automation levels (e.g. manual, semi- and fully-automated grafting) and eight scenarios are applied to a large-scale seedling propagator located in North America. Results demonstrate that (1) classic AHP produces the similar trend as fuzzy AHP, (2) the proposed BAS procedure can ensure the ranking accuracy of AHP, and (3) the proposed approach can be successfully used by vegetable seedling propagators to support the design of a grafting operation. © 2014 Elsevier B.V.
• Meng, C., Xu, D., Son, Y. -., Kubota, C. -., Lewis, M., & Tronstad, R. E. (2014). An Integrated Simulation and AHP Approach to Vegetable Grafting Operation Design. Computers and Electronics in Agriculture.
• Meng, C., Xu, D., Son, Y., Kubota, C., Lewis, M., & Tronstad, R. (2014). An integrated simulation and AHP approach to vegetable grafting operation design. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 102, 73-84.
• Son, Y. (2014). An extended bdi-based model for human decision-making and social behavior: Various applications. Studies in Computational Intelligence, 539, 171-174.
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  Abstract: An extended Belief-Desire-Intention (BDI) modeling framework has been developed and refined by the author's research group in the last decade to mimic realistic human decision-making and social behaviors. The goal of this manuscript is to discuss various applications that the proposed modeling framework has been applied, such as 1) evacuation behaviors under a terrorist bomb attack, 2) pedestrian behaviors in the Chicago Loop area, 3) workforce assignment in a multi-organizational social network for community-based software development, 4) pedestrian behaviors in a shopping mall, 5) evacuation behaviors under fire in a factory, and 6) error detection and resolution by people in a complex manufacturing facility. © 2014 Springer International Publishing Switzerland.
• Joo, J., Kim, N., Wysk, R. A., Rothrock, L., Son, Y., Oh, Y., & Lee, S. (2013). Agent-based simulation of affordance-based human behaviors in emergency evacuation. SIMULATION MODELLING PRACTICE AND THEORY, 32, 99-115.
• Joo, J., Kim, N., Wysk, R. A., Rothrock, L., Son, Y., Oh, Y., & Lee, S. (2013). Agent-based simulation of affordance-based human behaviors in emergency evacuation. Simulation Modelling Practice and Theory, 32, 99-115.
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  Abstract: Complex cognitive processes corresponding to human control behaviors cannot be easily inferred using (1) a logical rule-based model, (2) a statistical model, or (3) an analytical predictive model. Predicting human behaviors in complex and uncertain environments like emergency evacuation is considered almost impossible (at least NP hard) in systems theory. In this paper, we explore simulating human behaviors using affordance-based finite state automata (FSA) modeling, based on the ecological concept of affordance theory. To this end, we introduce the conceptual and generic framework of affordance-based human behavior simulation developed through our previous work. Following the generic framework, formal simulation models of affordance-based human behaviors are developed, especially for emergency evacuation, to mimic perception-based dynamic human actions interacting with emergent environmental changes, such as fire. A "warehouse fire evacuation" case is used to demonstrate the applicability of the proposed framework. The human action planning algorithms in the simulation model are developed and implemented using the Adjusted Floor Field Indicators, which represent not only the evacuee's prior knowledge of the floor layout but the perceivable information about dynamic environmental changes. The results of our simulation study verify that the proposed framework accurately simulates human fire evacuation behavior. The proposed framework is expected to capture the natural manner in which humans behave in emergency evacuation and enhance the simulation fidelity of analyses and predictions of perceptual human behaviors/responses in the systems by incorporating cognitive intent into human behavior simulations. © 2012 Elsevier B.V. All rights reserved.
• Khaleghi, A. M., Dong, X. u., Lobos, A., Minaeian, S., Son, Y., & Liu, J. (2013). Agent-based hardware-in-the-loop simulation for UAV/UGV surveillance and crowd control system. Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013, 1455-1466.
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  Abstract: An agent-based hardware-in-the-loop simulation framework is proposed to model the UAV/UGV surveillance and crowd control system. To this end, a planning and control system architecture is discussed first, which includes various modules such as sensory data collection, crowd detection, tracking, motion planning, control command generation, and control strategy evaluation. The modules that are highly related with agent-based modeling (focus of this paper) are then discussed, which includes the UAV/UGV motion planning considering multi-objectives, crowd motion modeling via social force model, and enhancement of simulation environment via GIS 3D coordinates conversion. In the experiment, Repast Simphony is used as the agent-based modeling tool, which transmits sensory data and control commands with QGroundControl as hardware interface that further conducts radio communications with ArduCopter as a real UAV. Preliminary results show that finer grid scale and larger vehicle detection range generate a better crowd coverage percentage. Finally, conclusions and future works are discussed. © 2013 IEEE.
• Khaleghi, A. M., Dong, X. u., Wang, Z., Mingyang, L. i., Lobos, A., Liu, J., & Son, Y. (2013). A DDDAMS-based planning and control framework for surveillance and crowd control via UAVs and UGVs. Expert Systems with Applications, 40(18), 7168-7183.
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  Abstract: A dynamic data driven adaptive multi-scale simulation (DDDAMS) based planning and control framework is proposed for effective and efficient surveillance and crowd control via UAVs and UGVs. The framework is mainly composed of integrated planner, integrated controller, and decision module for DDDAMS. The integrated planner, which is designed in an agent-based simulation (ABS) environment, devises best control strategies for each function of (1) crowd detection (vision algorithm), (2) crowd tracking (filtering), and (3) UAV/UGV motion planning (graph search algorithm). The integrated controller then controls real UAVs/UGVs for surveillance tasks via (1) sensory data collection and processing, (2) control command generation based on strategies provided by the decision planner for crowd detection, tracking, and motion planning, and (3) control command transmission via radio to the real system. The decision module for DDDAMS enhances computational efficiency of the proposed framework via dynamic switching of fidelity of simulation and information gathering based on the proposed fidelity selection and assignment algorithms. In the experiment, the proposed framework (involving fast-running simulation as well as real-time simulation) is illustrated and demonstrated for a real system represented by hardware-in-the-loop (HIL) real-time simulation integrating real UAVs, simulated UGVs and crowd, and simulated environment (e.g. terrain). Finally, the preliminary results successfully demonstrate the benefit of the proposed dynamic fidelity switching concerning the crowd coverage percentage and computational resource usage (i.e. CPU usage) under cases with two different simulation fidelities. © 2013 Elsevier Ltd. All rights reserved.
• Khaleghi, A. M., Xu, D., Lobos, A., Minaeian, S., Son, Y., & Liu, J. (2013). AGENT-BASED HARDWARE-IN-THE-LOOP SIMULATION FOR UAV/UGV SURVEILLANCE AND CROWD CONTROL SYSTEM. 2013 WINTER SIMULATION CONFERENCE (WSC), 1455-+.
• Khaleghi, A. M., Xu, D., Wang, Z., Li, M., Lobos, A., Liu, J., & Son, Y. (2013). A DDDAMS-based planning and control framework for surveillance and crowd control via UAVs and UGVs. EXPERT SYSTEMS WITH APPLICATIONS, 40(18), 7168-7183.
• Kim, S., Mungle, S., & Son, Y. (2013). An agent-based simulation approach for dual toll pricing of hazardous material transportation. Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013, 2520-2531.
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  Abstract: A dual toll pricing is a conceptual policy in which policy maker imposes toll on both hazardous materials (hazmat) vehicles as well as regular vehicles for using populated road segments to mitigate a risk of haz-mat transportation. It intends to separate the hazmat traffic flow from the regular traffic flow via controlling the dual toll. In order to design the dual toll pricing policy on a highly realistic road network environment and detailed human behaviors, an extended BDI framework is employed to mimic human decision behaviors in great detail. The proposed approach is implemented in AnyLogic® agent based simulation software with using a traffic data of Albany, NY. Also, search algorithms in OptQuest® are used to determine the optimum dual toll pricing policy which results in the minimum risk and travel cost based on the simulation results. The result reveals the effectiveness of the proposed approach in devising a reliable policy under the realistic road network conditions. © 2013 IEEE.
• Meng, C., Kim, S., Son, Y., & Kubota, C. (2013). A SysML-based simulation model aggregation framework for seedling propagation system. Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013, 2180-2191.
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  Abstract: This paper proposes a Systems Modeling Language (SysML)-based simulation model aggregation framework to develop aggregated simulation models with high accuracy. The framework consists of three major steps: 1) system conceptual modeling, 2) simulation modeling, and 3) additive regression model-based parameter estimation. SysML is first used to construct the system conceptual model for a generic seedling propagation system in terms of system structure and activities in a hierarchical manner (i.e. low, medium and high levels). Simulation models conforming to the conceptual model are then constructed in Arena. An additive regression model-based approach is proposed to estimate parameters for the aggregated simulation model. The proposed framework is demonstrated via one of the largest grafted seedling propagation systems in North America. The results reveal that 1) the proposed framework allows us to construct accurate but computationally affordable simulation models for seedling propagation system, and 2) model aggregation increases the randomness of simulation outputs. © 2013 IEEE.
• Meng, C., Nageshwaraniyer, S. S., Maghsoudi, A., Son, Y., & Dessureault, S. (2013). Data-driven modeling and simulation framework for material handling systems in coal mines. COMPUTERS & INDUSTRIAL ENGINEERING, 64(3), 766-779.
• Meng, C., Nageshwaraniyer, S. S., Maghsoudi, A., Son, Y., & Dessureault, S. (2013). Data-driven modeling and simulation framework for material handling systems in coal mines. Computers and Industrial Engineering, 64(3), 766-779.
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  Abstract: In coal mining industry, discrete-event simulation has been widely used to support decisions in material handling system (MHS) to achieve premiums on revenues. However, the conventional simulation modeling approach requires extensive expertise of simulation during the modeling phase and lacks flexibility when the MHS structure changes. In this paper, a data-driven modeling and simulation framework is developed for MHS of coal mines to automatically generate a discrete-event simulation model based on current MHS structural and operational data. To this end, a formal information model based on Unified Modeling Language (UML) is first developed to provide MHS structural information for simulation model generation, production information for simulation execution, and output requirement information for defining simulation outputs. Then, Petri net-based model generation procedures are designed and used to automatically generate a simulation model in Arena® based on the simulation inputs conforming to the constructed information model. The proposed framework is demonstrated for one of the largest open-pit coal mines in the USA, and it has been demonstrated that the framework can be used to effectively generate the simulation models that precisely represent MHS of coal mines, and then be used to support various decisions in coal mining such as equipment scheduling. © 2013 Elsevier Ltd. All rights reserved.
• Mungle, S., Benyoucef, L., Son, Y., & Tiwari, M. K. (2013). A fuzzy clustering-based genetic algorithm approach for time-cost-quality trade-off problems: A case study of highway construction project. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 26(8), 1953-1966.
• Mungle, S., Benyoucef, L., Son, Y., & Tiwari, M. K. (2013). A fuzzy clustering-based genetic algorithm approach for time-cost-quality trade-off problems: A case study of highway construction project. Engineering Applications of Artificial Intelligence, 26(8), 1953-1966.
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  Abstract: Recently government agencies have started to utilize innovative contracting methods that provide incentives for improving construction quality. These emerging contracting methods place an enormous pressure on the contractors to improve construction quality. For a general contractor, which subcontracts most tasks of a project and invites a number of bids, choosing an appropriate bid which satisfies the time, cost and quality of construction project is complex and challenging. To solve this problem involving conflicting objectives, a fuzzy clustering-based genetic algorithm (FCGA) approach is proposed in this paper. A case study of highway construction is used to demonstrate the applicability of the proposed approach. A comparative study is conducted over three test cases involving varying dimensions and complexities to test performance of the proposed FCGA against existing approaches. Results reveal that the FCGA is capable of generating better Pareto front than other existing approaches. © 2013 Elsevier Ltd. All rights reserved.
• Nageshwaraniyer, S. S., Khilwani, N., Tiwari, M. K., Shankar, R., & Ben-Arieh, D. (2013). Solving the design of distributed layout problem using forecast windows: A hybrid algorithm approach. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 29(1), 128-138.
• Nageshwaraniyer, S. S., Son, Y., & Dessureault, S. (2013). SIMULATION-BASED ROBUST OPTIMIZATION FOR COMPLEX TRUCK-SHOVEL SYSTEMS IN SURFACE COAL MINES. 2013 WINTER SIMULATION CONFERENCE (WSC), 3522-3532.
• Nageshwaraniyer, S. S., Son, Y., & Dessureault, S. (2013). Simulation-based optimal planning for material handling networks in mining. SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL, 89(3), 330-345.
• Nageshwaraniyer, S. S., Son, Y., & Dessureault, S. (2013). Simulation-based optimal planning for material handling networks in mining. Simulation, 89(3), 330-345.
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  Abstract: A two-level hierarchical simulation-based framework is proposed for real-time planning in one of the largest coal mines in the world. At the coal mine, various decisions (e.g. truck locks, hopper-silo connections and silo blend values) have to be made to ship coal to customers via trains. To resolve machinery scheduling and train loading problems in an integrated manner, mathematical formulations are developed and embedded within the proposed hierarchical framework. At the upper level, the coal flow in the simulation model is directly from pits to trains and in the lower level a full simulation model of the coal mine is used for simulating the flow of coal from pits to hoppers via trucks, then from hoppers to silos and silos to loadouts via conveyors. In this work, Arena software is used for the simulation model: it retrieves real-time status and historical performance data from Microsoft SQL Server situated remotely at the coal mine. OptQuest software is used to resolve optimization problems. Finally, two types of experiments are conducted to illustrate the performance of the proposed framework for the actual coal mine. Firstly, the bounds of the constraints in the upper level are varied to study the behavior of the total revenue in shift and revenue by train. Secondly, the effects of increasing variations in truck travel times, loading and dumping rates on machine utilization are studied at the lower level. © 2012 The Society for Modeling and Simulation International.
• Nageshwaraniyer, S. S., Son, Y., & Dessureault, S. (2013). Simulation-based robust optimization for complex truck-shovel systems in surface coal mines. Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013, 3522-3532.
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  Abstract: A robust simulation-based optimization approach is proposed for truck-shovel systems in surface coal mines to maximize the expected value of revenue obtained from customer trains. To this end, a large surface coal mine in North America is considered as case study, and a highly detailed simulation model of that mine is constructed in Arena. Factors encountered in material handling operations that may affect the robustness of revenue are then classified into 1) controllable, 2) uncontrollable and 3) constant categories. Historical production data of the mine is used to derive probability distributions for the uncontrollable factors. Then, Response Surface Methodology is applied to derive an expression for the variance of revenue under the influence of controllable and uncontrollable factors. The resulting variance expression is applied as a constraint to the mathematical formulation for optimization using OptQuest. Finally, coal production is observed under variation in number of trucks and down events. © 2013 IEEE.
• Son, Y., Kim, S., Hui, X. i., & Mungle, S. (2013). An extended BDI model for human behaviors: Decision-making, learning, interactions, and applications. Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013, 401-411.
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  Abstract: Modeling human decision-making behaviors under a complex and uncertain environment is quite challenging. The goal of this tutorial is to discuss an extended Belief-Desire-Intention (BDI) framework that the authors' research group has been developing last decade to meet such a challenge, integrating models and techniques (e.g. Bayesian Belief Network, Decision Field Theory, Depth First Search) available in the fields of engineering, psychology, computational science, and statistics. First, major modules of the extended BDI framework are discussed, where those modules represent cognitive functions (i.e. perception, goal seeking, planning, decision-making, execution) of an individual. Then, two extensions are considered, where the first one involves dynamic evolution of underlying modules over time (i.e. learning and forgetting), and the second one involves human interactions (e.g. competition, collaboration, compromise, accommodation, avoidance). To illustrate the proposed approach, various applications are used, such as emergency evacuation during bomb attack, driver and pedestrian behaviors, and cyber social network. © 2013 IEEE.
• Sáenz, J. P., Celik, N., Hui, X. i., Son, Y., & Asfour, S. (2013). Two-stage economic and environmental load dispatching framework using particle filtering. International Journal of Electrical Power and Energy Systems, 48(1), 93-110.
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  Abstract: Economic load dispatch (ELD) is the operation of generation plants producing reliable electricity at the lowest cost, while recognizing limitations of the system. The environmental economic load dispatch (EELD) problem extends the ELD to include environmental considerations which makes it even more challenging due to the fact that it considers a very large scale and dynamic system that is highly complex and has inherent uncertainty. In this study, we propose a novel two-stage economic and environmental load dispatching framework using particle filtering for the efficient and reliable dynamic dispatching of electricity under uncertainty. The proposed framework includes (1) a short term demand forecasting algorithm using wavelet transform adaptive modeling, and (2) a dynamic load dispatching algorithm using particle filtering developed in a simulation environment. The proposed approach has been successfully demonstrated for different scenarios in the original IEEE-30 bus test system, which has been benchmarked against contemporary models available in the literature; and a modified version of the IEEE-30 bus test system, where the loads are modeled to update according to the weather and other external conditions. © 2012 Elsevier Ltd. All rights reserved.
• Zhao, J., Kucuksari, S., Mazhari, E., & Son, Y. (2013). Integrated analysis of high-penetration PV and PHEV with energy storage and demand response. APPLIED ENERGY, 112, 35-51.
• Zhao, J., Kucuksari, S., Mazhari, E., & Son, Y. (2013). Integrated analysis of high-penetration PV and PHEV with energy storage and demand response. Applied Energy, 112, 35-51.
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  Abstract: The increasing utilization of Plug-in Hybrid Electric Vehicles (PHEVs) in future will have significant impact on utility companies and customers depending on their charging characteristics. Uncontrolled or unscheduled vehicle charging may increase the residential peak and the risk of electric distribution network failure. In order to reduce the peak load utility companies encourage customers who have such high electricity consuming devices to participate in various demand response (DR) programs. Additionally, considering increasing Photovoltaic (PV) generation and storage facility installation on customer side, the integration of PHEVs needs more attention as system's performance becomes highly fluctuating and unpredictable. This paper presents a simulation based optimization framework for integrated analysis of demand response programs, with high penetration of PHEV and PV and storage systems from residential customer's perspective as well as utility company's perspective. An agent-based simulation model is built in AnyLogic to mimic the household load, PHEV charging, PV generation and storage together with various demand response programs such as time-of-use (TOU), Real-time Pricing (RTP), and curtailment. In the considered scenarios, customers schedule their PHEV charging time and duration to minimize the electricity bill considering the price at the time of use, while the utility company aims to minimize the peak due to the PHEV charging by changing prices. The constructed simulation helps the utility company identify the best policies, and helps customers make better response under different DR programs. Three demand response programs are simulated with and without PV and storage. Results show that the simulation model successfully represents the cases and appropriate scheduling has benefits for both customers and utility companies. © 2013 Elsevier Ltd.
• Bloomfield, R., Mazhari, E., Hawkins, J., & Son, Y. (2012). Interoperability of manufacturing applications using the Core Manufacturing Simulation Data (CMSD) standard information model. COMPUTERS & INDUSTRIAL ENGINEERING, 62(4), 1065-1079.
• Bloomfield, R., Mazhari, E., Hawkins, J., & Son, Y. (2012). Interoperability of manufacturing applications using the Core Manufacturing Simulation Data (CMSD) standard information model. Computers and Industrial Engineering, 62(4), 1065-1079.
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  Abstract: The goal of this paper is to propose an approach to enhance interoperability between manufacturing applications using the Core Manufacturing Simulation Data Information Model (CMSDIM) in order to streamline design and manufacturing activities throughout the product life cycle. To this end, a system framework required to facilitate such interoperability is first presented. The proposed approach, architecture, and developed translators are then illustrated and demonstrated using two separate case studies. The first case study facilitates design for manufacturing and assembly improvements for the development of new products, allowing for part of a discrete event simulation model of a downstream manufacturing and assembly process to be automatically generated from corresponding product assembly information contained in the lean design engineering software. Conceptual design and development of this case study, which extracts outputs from Design Profit™ lean design software and generates a corresponding discrete event simulation model in ProModel™ for a Nikon® L-100 Camera, is then discussed. The second case study demonstrates interoperability of three applications (order and inventory system, Gantt chart scheduler, and discrete event simulation) for a generic job shop operation. Using the considered case studies, this paper also details and demonstrates the benefits of interoperability enhancement using the CMSDIM, which is an important consideration in any product life cycle. Finally, we discuss how future research opportunities integrating additional manufacturing applications can be used to address intellectual challenges present in our current approach. © 2011 Elsevier Ltd. All rights reserved.
• Celik, N., & Son, Y. (2012). Sequential Monte Carlo-based fidelity selection in dynamic-data-driven adaptive multi-scale simulations. International Journal of Production Research, 50(3), 843-865.
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  Abstract: In a simulation-based planning and control framework, timely monitoring, analysis, and control is important not to disrupt a dynamically changing system. To meet this temporal requirement, a dynamic-data-driven adaptive multi-scale simulation (DDDAMS) paradigm was proposed earlier, where the fidelity of a complex simulation model adapts to available computational resources by incorporating dynamic data into the executing model, which then steers the measurement process for selective data update. In this work, a sequential Monte Carlo method (sequential Bayesian inference technique) is proposed and embedded into the simulation to enable its ideal fidelity selection given massive datasets under the DDDAMS framework. As dynamic information becomes available, the proposed method makes efficient inferences to determine the sources of abnormality in the system (a shop floor in this paper). A parallelisation framework is also discussed to further reduce the number of data accesses while maintaining the accuracy of parameter estimates. A prototype DDDAMS involving the proposed algorithm has been implemented successfully for preventive maintenance scheduling and part routing scheduling in a semiconductor manufacturing supply chain, reducing the average waiting time of batches and increasing the machine utilisation significantly. © 2012 Taylor & Francis.
• Celik, N., Hui, X. i., Dong, X. u., Son, Y., Lemaire, R., & Provan, K. (2012). Simulation-based workforce assignment considering position in a social network. Simulation, 88(1), 72-96.
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  Abstract: The goal of this paper is to propose a novel modeling framework to help project managers devise optimal workforce assignments that consider both short- and long-term aspects of projects that must be completed through a multi-organizational social network. The proposed framework is comprised of an evaluation module and an assignment module. Each time a workforce assignment is performed, the Decision Evolution Procedure of the evaluation module first calculates the position value between each pair of currently available workforce members based on various social networking parameters such as trustworthiness, influence, reputation, and proximity. Second, by using these position values, the Extended Regular Equivalence Evaluation algorithm from the evaluation module computes the regular and structural equivalence values between each pair of workforce members. Finally, the assignment module selects an optimal workforce mix that maximizes both the short-term performance (productivity) as well as the long-term performance (workforce training, and robustness) of the project organizations. Agent-based simulation and multi-objective optimization techniques are leveraged for the evaluation module and the assignment module, respectively. The proposed framework is illustrated and successfully demonstrated using the software enhancement request process in Kuali, a multi-organizational alliance-based software development project involving 12 universities. © Simulation Councils Inc. 2012.
• Celik, N., Nageshwaraniyer, S. S., & Son, Y. (2012). Impact of information sharing in hierarchical decision-making framework in manufacturing supply chains. JOURNAL OF INTELLIGENT MANUFACTURING, 23(4), 1083-1101.
• Celik, N., Nageshwaraniyer, S. S., & Son, Y. (2012). Impact of information sharing in hierarchical decision-making framework in manufacturing supply chains. Journal of Intelligent Manufacturing, 23(4), 1083-1101.
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  Abstract: This paper presents a comprehensive framework for the analysis of the impact of information sharing in hierarchical decision-making in manufacturing supply chains. In this framework, the process plan selection and real-time resource allocation problems are formulated as hierarchical optimization problems, where problems at each level in the hierarchy are solved by separate multi-objective genetic algorithms. The considered multi-objective genetic algorithms generate near optimal solutions for NP-hard problems with less computational complexity. In this work, a four-level hierarchical decision structure is considered, where the decision levels are defined as enterprise level, shop level, cell level, and equipment level. Using this framework, the sources of information affecting the achievement of best possible decisions are then identified at each of these levels, and the extent of their effects from sharing them are analyzed in terms of the axis, degree and the content of information. The generality and validity of the proposed approach have been successfully tested for diverse manufacturing systems generated from a designed experiment. © 2010 Springer Science+Business Media, LLC.
• Hui, X. i., & Son, Y. (2012). Two-level modeling framework for pedestrian route choice and walking behaviors. Simulation Modelling Practice and Theory, 22, 28-46.
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  Abstract: A microscopic two-level simulation modeling framework is proposed to analyze both decision-making processes at a crosswalk as well as physical interactions among pedestrians when they cross a street. The model at the higher level is based on Decision Field Theory to represent the psychological preferences of pedestrians with respect to different route choice options during their deliberation process after evaluating current surroundings. At the lower level, physical interactions among pedestrians and consequent congestions are represented using a Cellular Automata model, in which pedestrians are allowed biased random-walking without back step towards their destination that has been given by the higher level model. A typical crosswalk with split sidewalks in the Chicago Loop area is employed as a case study, which has been implemented in AnyLogic® software. Weekday pedestrian counts on the 15-min basis near the studied crosswalk have been collected and used to construct and validate the simulation models. Experiments have been conducted to investigate the impact of corresponding environment parameters, such as pedestrian types and green/red phase length, as well as social parameters such as leadership in group decision making, on the average pedestrian waiting time at the crosswalk. Initial results look quite interesting. An extension on coupling the proposed pedestrian model with a transportation simulation model is also briefly discussed. © 2011 Elsevier B.V. All rights reserved.
• Kim, D. Y., Xirouchakis, P., & Son, Y. J. (2012). Compatible component selection under uncertainty via extended constraint satisfaction approach. International Journal of Industrial Engineering : Theory Applications and Practice, 19(12), 464-474.
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  Abstract: This paper deals with compatible component selection problems, where the goal is to find combinations of components satisfying design constraints given a product structure, component alternatives available in design catalogue for each subsystem of the product, and a preliminary design constraint. An extended Constraint Satisfaction Problem (CSP) is introduced to solve component selection problems considering uncertainty in the values of design variables. To handle a large number of all possible combinations of components, the paper proposes a systematic filtering procedure and an efficient method to estimate a complex feasible design space to facilitate selection of component combinations having more feasible solutions. The proposed approach is illustrated and demonstrated with a robotic vacuum cleaner design example. © International Journal of Industrial Engineering.
• Ryu, K., Lee, S., Klm, D., & Son, Y. (2012). A novel modeling methodology for collaborative enterprise processes. International Journal of Innovative Computing, Information and Control, 8(7 B), 5369-5380.
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  Abstract: This paper proposes an extended collaborative process modeling (exCPM), underpinned, by the concepts of tokens in Petri Nets (PNs) and ICOM in IDEFO. exCPM allows us to represent collaborative processes in a more comprehensive manner than CPM. In addition, it provides a systematic model verification procedure by model transformation into PNs. In this paper, we first analyze pros and cons of currently available process modeling methods. We then discuss details of the proposed exCPM, and demonstrate its modeling and verification capabilities with case studies. © 2012 ICIC International.
• Sáenz, J. P., Celik, N., Asfour, S., & Son, Y. (2012). Electric utility resource planning using Continuous-Discrete Modular Simulation and Optimization (CoDiMoSO). Computers and Industrial Engineering, 63(3), 671-694.
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  Abstract: Electric utility resource planning traditionally focuses on conventional energy supplies such as coal, natural gas, and oil. Nowadays, planning of renewable energy generation as well as its side necessity of storage capacities have become equally important due to the increasing growth in energy demand, insufficiency of natural resources, and newly established policies for low carbon footprint. In this study, we propose to develop a comprehensive simulation based decision making framework to determine the best possible combination of resource investments for electric power generation and storage capacities. The proposed tool involves a combined continuous-discrete modular modeling approach for processes of different nature that exist within this complex system, and will help the utility companies conduct resource planning via employed multiobjective optimization techniques in a realistic simulation environment. The distributed power system considered here has four major components including (1) energy generation via a solar farm, a wind farm, and a fossil fuel power station, (2) storage via compressed air energy storage system, and batteries, (3) transmission via a bus and two main substations, and (4) demand of industrial, commercial, residential and transportation sectors. The proposed approach has been successfully demonstrated for the electric utility resource planning at a scale of the state of Florida. © 2011 Elsevier Ltd. All rights reserved.
• Xi, H., & Son, Y. (2012). Two-level modeling framework for pedestrian route choice and walking behaviors. SIMULATION MODELLING PRACTICE AND THEORY, 22, 28-46.
• Celik, N., & Son, Y. (2011). State estimation of a shop floor using improved resampling rules for particle filtering. International Journal of Production Economics, 134(1), 224-237.
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  Abstract: Operational inefficiencies in supply chains cost industries millions of dollars every year. Much of these inefficiencies arise due to the lack of a coherent planning and control mechanism, which requires accurate yet timely state estimation of these large-scale dynamic systems given their massive datasets. While Bayesian inferencing procedures based on particle filtering paradigm may meet these requirements in state estimation, they may end up in a situation called degeneracy, where a single particle abruptly possesses significant amount of normalized weights. Resampling rules for importance sampling prevent the sampling procedure from generating degenerated weights for particles. In this work, we propose two new resampling rules concerning minimized variance (VRR) and minimized bias (BRR). The proposed rules are derived theoretically and their performances are benchmarked against that of the minimized variance and half-width based resampling rules existing in the literature using a simulation of a semiconductor die manufacturing shop floor in terms of their resampling qualities (mean and variance of root mean square errors) and computational efficiencies, where we identify the circumstances that the proposed resampling rules become particularly useful. © 2011 Elsevier B.V.
• Celik, N., Lee, S., Mazhari, E., Son, Y., Lemaire, R., & Provan, K. G. (2011). Simulation-based workforce assignment in a multi-organizational social network for alliance-based software development. Simulation Modelling Practice and Theory, 19(10), 2169-2188.
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  Abstract: The development of alliance-based software requires the collaboration of many stakeholders. These different stakeholders across multiple organizations form a complex social network. The goal of this paper is to develop a novel modeling framework, which will help task managers devise optimal workforce assignments considering both short-term and long-term aspects of the software development process. The proposed framework is composed of an assignment module and a prediction module. For a given task, the assignment module first selects a candidate workforce mix. Based on the candidate workforce mix, the prediction module then predicts the short-term performance (productivity) as well as the long-term performance (workforce training and robustness of the organization) of the organization. Then, the assignment module selects another candidate mix, and this iteration continues until an optimal workforce mix is found. The prediction module and the assignment module are based on an agent-based simulation method and a multi-objective optimization model, respectively. The proposed modeling framework is illustrated with a software enhancement request process in Kuali, an alliance-based open source software development project involving 12 organizations. The constructed framework is executed with varying parameters to demonstrate its use and benefit in the software enhancement process. © 2011 Elsevier B.V. All rights reserved.
• Corredor, J. S., Celik, N., Asfour, S., & Son, Y. (2011). Utility resource planning using modular simulation and optimization. Proceedings - Winter Simulation Conference, 963-975.
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  Abstract: Electric utility resource planning traditionally focuses on conventional energy supplies. Nowadays, planning of renewable energy generation and its storage has become equally important due to the growth in demand, insufficiency of natural resources, and policies for low carbon footprint. We propose to develop a simulation based decision making framework to determine the best possible combination of investments for electric power generation and storage capacities. The proposed tool involves a combined continuous-discrete modular modeling approach for processes of different nature within this complex system, and will aid utility companies in resource planning via multi-objective optimization in a realistic simulation environment. The distributed power system considered has four components including energy generation, storage, transmission, and electricity demand. The proposed approach has been demonstrated for the electric utility resource planning at a scale of the state of Florida. © 2011 IEEE.
• Dong, X. u., Nageshwaraniyer, S. S., Son, Y., & Song, S. (2011). Simulation-based assessment of change propagation effect in an aircraft design process. Proceedings - Winter Simulation Conference, 1710-1721.
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  Abstract: In the current work, a simulation-based approach is proposed to assess the change propagation effect in an aircraft design process. To this end, three extensions are made to the conventional approach using design structure matrix to model change propagation effect. They are: 1) logistics factor associated with the component supplies of aircraft; 2) manufacturing system flexibility factor; 3) uncertainty in design change parameters. Then the effects of change propagation are simulated using a discrete-event simulation model in Arena involving detailed design process of totally eight components of a real aircraft. Finally, what-if analyses are performed by varying logistics and flexibility factors under uncertainty in design change parameters to assess the change propagation effect. An optimization problem is also solved using OptQuest to determine the change propagation path that minimizes the total risk of design change. Future work is discussed for extending the proposed approach to other related areas. © 2011 IEEE.
• Kim, N., Joo, J., Rothrock, L., Wysk, R., & Son, Y. (2011). Human behavioral simulation using affordance-based agent model. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6761 LNCS(PART 1), 368-377.
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  Abstract: In this paper, we propose a novel agent-based simulation modeling of human behaviors. A conceptual framework of human behavioral simulation is suggested using the ecological definition of affordances in order to mimic perception-based human actions interacting with the environment. A simulation example of a 'warehouse fire evacuation' is illustrated to demonstrate the applicability of the proposed framework. The perception-based human behaviors and planning algorithms are adapted and embedded within human agent models using the Static and Dynamic Floor Field Indicators, which represent the evacuee's prior knowledge of the floor layout and perceivable information of dynamic environmental changes, respectively. The proposed framework is expected to capture the natural manners in which humans participate in systems and enhance the simulation fidelity by incorporating cognitive intent into human behavior simulations. © 2011 Springer-Verlag.
• Mazhari, E., Zhao, J., Celik, N., Lee, S., Son, Y., & Head, L. (2011). Hybrid simulation and optimization-based design and operation of integrated photovoltaic generation, storage units, and grid. SIMULATION MODELLING PRACTICE AND THEORY, 19(1), 463-481.
• Mazhari, E., Zhao, J., Celik, N., Lee, S., Son, Y., & Head, L. (2011). Hybrid simulation and optimization-based design and operation of integrated photovoltaic generation, storage units, and grid. Simulation Modelling Practice and Theory, 19(1), 463-481.
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  Abstract: Unlike fossil-fueled generation, solar energy resources are geographically distributed and highly intermittent, which makes their direct control extremely difficult and requires storage units as an additional concern. The goal of this research is to design and develop a flexible tool, which will allow us to obtain (1) an optimal capacity of an integrated photovoltaic (PV) system and storage units and (2) an optimal operational decision policy considering the current and future market prices of the electricity. The proposed tool is based on hybrid (system dynamics model and agent-based model) simulation and meta-heuristic optimization. In particular, this tool has been developed for three different scenarios (involving different geographical scales), where PV-based solar generators, storage units (compressed-air-energy-storage (CAES) and super-capacitors), and grid are used in an integrated manner to supply energy demands. Required data has been gathered from various sources, including NASA and TEP (utility company), US Energy Information Administration, National Renewable Energy Laboratory, commercial PV panel manufacturers, and publicly available reports. The constructed tool has been demonstrated to (1) test impacts of several factors (e.g. demand growth, efficiencies in PV panel and CAES system) on the total cost of the integrated generation and storage system and an optimal mixture of PV generation and storage capacity, and to (2) demonstrate an optimal operational policy. © 2010 Elsevier B.V. All rights reserved.
• Nageshwaraniyer, S. S., Celik, N., Son, Y., & Roberto, L. u. (2011). Simulation-Based Aircraft Assembly Planning Using a Self-Guided Ant Colony Algorithm. Evolutionary Computing in Advanced Manufacturing, 169-195.
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  Abstract: The aerospace industry plays a key role in today's U.S. economy with its total sales comprising 1.4% of the U.S. gross domestic product. The increasing competition in the aerospace industry between domestic and foreign competitors is motivating aerospace companies to seek for new and innovative ways to decrease the costs and lead-time for new product development and production by implementing flexible and integrated assembly systems. In this work, we present a simulationbased optimization framework for aircraft assembly planning using a self-guided ant colony algorithm (SGAC), where the objective is to achieve line balancing in the assembly of aircraft. More specifically, the goal is to minimize the number of workstations and maximize average utilization of resources in the stages of assembly. Based on the current state of the facility, the framework devises an optimal assembly plan. This plan is executed until the next time interval when the framework is again invoked to deliver the optimal assembly plan. The generality and validity of the proposed approach have been successfully tested for aircraft assembly planning under various conditions via a designed experiment. © 2011 Scrivener Publishing LLC. All rights reserved.
• Nageshwaraniyer, S. S., Meng, C., Son, Y., & Dessureault, S. (2011). SIMULATION-BASED UTILITY ASSESSMENT OF REAL-TIME INFORMATION FOR SUSTAINABLE MINING OPERATIONS. PROCEEDINGS OF THE 2011 WINTER SIMULATION CONFERENCE (WSC), 871-882.
• Nageshwaraniyer, S. S., Meng, C., Son, Y., & Dessureault, S. (2011). Simulation-based utility assessment of real-time information for sustainable mining operations. Proceedings - Winter Simulation Conference, 871-882.
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  Abstract: In capital intensive industries such as coalmines, real-time information is useful to run their operations within sustainable limits, and to enable early detection and response to deviations from those limits. The goal of this research is to assess the utilities of real-time information collected in coalmines for operating within sustainable limits. In this work, one of the largest coalmines in North America is considered. Utility indices are first proposed for important real-time information from the coalmine. Attributes are then defined for the indices and expressions for utility are proposed. The indices are also classified based on their impact on economic, social or environmental dimensions of sustainability of the coalmine. Experiments are conducted using real-time data on a simulation model of the material handling network of the coalmine to assess one of the proposed indices. The proposed index is found to precisely indicate utility of the corresponding real-time information. © 2011 IEEE.
• Rothrock, L., Wysk, R., Kim, N., Shin, D., Son, Y., & Joo, J. (2011). A modelling formalism for human-machine cooperative systems. International Journal of Production Research, 49(14), 4263-4273.
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  Abstract: This paper presents a collection of models of humans involved in complex systems with a focus on control of the system while allowing human participation in decisions for system operation. The existence of a formal model that captures human behaviour in a complex system allows for the efficient development of modelling and control software of man-machine systems. This paper provides a foundation for modelling and software development for complex systems that includes human activities. A modelling formalism, based on the automata theory for human-machine cooperative systems is demonstrated in this paper in consideration with the ecological concept of affordance. © 2011 Taylor & Francis.
• Vasudevan, K., & Son, Y. (2011). Concurrent consideration of evacuation safety and productivity in manufacturing facility planning using multi-paradigm simulations. COMPUTERS & INDUSTRIAL ENGINEERING, 61(4), 1135-1148.
• Vasudevan, K., & Son, Y. (2011). Concurrent consideration of evacuation safety and productivity in manufacturing facility planning using multi-paradigm simulations. Computers and Industrial Engineering, 61(4), 1135-1148.
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  Abstract: Manufacturing facilities are expected to maintain a high level of production and at the same time, employ strict safety standards to ensure the safe evacuation of the people in the event of emergencies (fire is considered in this paper). These two goals are often conflicting. This paper presents a methodology to evaluate evacuation safety versus productivity concurrently for various, widely known manufacturing layouts. While the safety performance indicators such as evacuation times are inferred from the crowd (agent based) simulation, the productivity performance indicators (e.g. throughput) are analyzed using the discrete event simulation. To this end, this research focuses on creating innovative techniques for developing accurate crowd simulations, where Belief-Desire-Intention (BDI) agent framework is employed to build each person's individual actions and the interactions between them. The data model and rule based action algorithms for each agent are reverse-engineered from the human-in-the-loop experiments in the immersive virtual reality environments. Finally, experiments are conducted using the constructed simulations to compare safety and productivity for different layouts. To demonstrate the proposed methodology, an automotive power-train (engine and transmission) manufacturing plant was used. Initial results look quite promising. © 2011 Elsevier Ltd. All rights reserved.
• Xu, D., Nageshwaraniyer, S. S., Son, Y., & Song, S. (2011). SIMULATION-BASED ASSESSMENT OF CHANGE PROPAGATION EFFECT IN AN AIRCRAFT DESIGN PROCESS. PROCEEDINGS OF THE 2011 WINTER SIMULATION CONFERENCE (WSC), 1710-1721.
• Zhao, J., Mazhari, E., Celik, N., & Son, Y. (2011). Hybrid agent-based simulation for policy evaluation of solar power generation systems. SIMULATION MODELLING PRACTICE AND THEORY, 19(10), 2189-2205.
• Zhao, J., Mazhari, E., Celik, N., & Son, Y. (2011). Hybrid agent-based simulation for policy evaluation of solar power generation systems. Simulation Modelling Practice and Theory, 19(10), 2189-2205.
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  Abstract: To encourage the adoption of solar power as well as new technological improvements in solar industry, state and federal governments have employed various kinds of incentives over the past decades, such as rebates, tax return opportunities, and Net Metering credits. At the same time, however, the governments concern regulations to avoid highly steep growth of solar energy without considering necessary supporting structure such as storage components, which will increase the electricity price and threaten the stability of existing transmission systems. The goal of this research is to develop a decision support tool to analyze the effectiveness of various policies (both incentives as well as regulations) on the proper growth rate of distributed photovoltaic (PV) systems avoiding the instability of the transition system or steep rising of the electricity price. To this end, we propose a hybrid two-level simulation modeling framework, which is significantly more detailed than the simplified structures commonly used in most policy evaluations. The lower-level model concerns the calculation of PV system payback period of individual household based on hourly electricity generation (PV) and consumptions, incentive levels, PV module price, and hourly electricity price (grid). The higher-level model, running on a weekly basis for 20 years, concerns the household adoption behaviors of the PV systems influenced by various factors, including payback period, household income, word-of-mouth effect and advertisement effect. Agent-based and system dynamics modeling techniques are leveraged in both levels. The proposed models have been developed for residential areas at two different regions in the US based on real data, which have been used to illustrate the impact of policies in different regions. © 2011 Elsevier B.V. All rights reserved.
• Celik, N., & Son, Y. (2010). State estimation of a supply chain using improved resampling rules for particle filtering. Proceedings - Winter Simulation Conference, 1998-2010.
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  Abstract: Resampling rules for importance sampling play a critical role in achieving good performance of the particle filters by preventing the sampling procedure from generating degenerated weights for particles, where a single particle abruptly possesses significant amount of normalized weights, and from wasting computational resources by replicating particles proportional to these weights. In this work, we propose two new resampling rules concerning minimized variance and minimized bias, respectively. Then, we revisit a half-with based resampling rule for benchmarking purposes. The proposed rules are derived theoretically and their performances are compared with that of the minimized variance and half width-based resampling rules existing in the literature using a supply chain simulation in terms of their resampling qualities (mean and variance of root mean square errors) and computational efficiencies, where we identify the circumstances that the proposed resampling rules become particularly useful. ©2010 IEEE.
• Celik, N., Hui, X. i., Dong, X. u., & Son, Y. (2010). Simulation-based workforce assignment considering position in a social network. Proceedings - Winter Simulation Conference, 3228-3240.
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  Abstract: Globally distributed software enhancement necessitates joint efforts of workforces across various organizations, which constitutes a multifaceted social network. Here, we propose a novel modeling framework to optimally assign the workforce to software development projects considering both short and long-term benefits of the organization. The proposed framework is composed of the evaluation module, an agent-based simulation model representing the considered social network; and the assignment module, a multi-objective optimization model. The Decision Evolution Procedure of the evaluation module first calculates the position values between each pair of available workforce. Using these position values, the Extended Regular Equivalence Evaluation algorithm of the evaluation module then computes the regular and structural equivalence values between each pair of workforce. Finally, the assignment module selects the optimal workforce mix maximizing both the short (productivity) and long-term performance (robustness) of the organization. The proposed framework is demonstrated with the software enhancement process in Kuali organizational network. ©2010 IEEE.
• Celik, N., Lee, S., Vasudevan, K., & Son, Y. (2010). DDDAS-based multi-fidelity simulation framework for supply chain systems. IIE TRANSACTIONS, 42(5), 325-341.
• Celik, N., Lee, S., Vasudevan, K., & Son, Y. (2010). DDDAS-based multi-fidelity simulation framework for supply chain systems. IIE Transactions (Institute of Industrial Engineers), 42(5), 325-341.
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  Abstract: Dynamic-Data-Driven Application Systems (DDDAS) is a new modeling and control paradigm which adaptively adjusts the fidelity of a simulation model. The fidelity of the simulation model is adjusted against available computational resources by incorporating dynamic data into the executing model, which then steers the measurement process for selective date update. To this end, comprehensive system architecture and methodologies are first proposed, where the components include a real-time DDDAS simulation, grid modules, a web service communication server, databases, various sensors and a real system. Abnormality detection, fidelity selection, fidelity assignment, and prediction and task generation are enabled through the embedded algorithms developed in this work. Grid computing is used for computational resources management and web services are used for inter-operable communications among distributed software components. The proposed DDDAS is demonstrated on an example of preventive maintenance scheduling in a semiconductor supply chain. Copyright © "IIE".
• Chan, W., Son, Y., & Macal, C. M. (2010). AGENT-BASED SIMULATION TUTORIAL - SIMULATION OF EMERGENT BEHAVIOR AND DIFFERENCES BETWEEN AGENT-BASED SIMULATION AND DISCRETE-EVENT SIMULATION. PROCEEDINGS OF THE 2010 WINTER SIMULATION CONFERENCE, 135-150.
• Hui, X. i., Son, Y., & Lee, S. (2010). An integrated pedestrian behavior model based on extended decision field theory and social force model. Proceedings - Winter Simulation Conference, 824-836.
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  Abstract: A novel pedestrian behavior model is proposed, which integrates 1) Extended Decision Field Theory (EDFT) for tactical level human decision-making, 2) Social Force model (SFM) to represent physical interactions and congestions among the people and the environment, and 3) dynamic planning algorithm involving AND/OR graphs. Furthermore, the Social Force model is enhanced with the vision of each individual, and both individual behaviors as well as group behaviors are considered. The proposed model is illustrated and demonstrated with a shopping mall scenario. Literature survey and observations have been conducted at the mall for data collection and partial validation of the proposed model. The constructed simulation using AnyLogic® software was utilized to conduct several experiments on performance of the mall and scalability of the proposed model. ©2010 IEEE.
• Kin, W., Son, Y., & Macal, C. M. (2010). Agent-based simulation tutorial - Simulation of emergent behavior and differences between agent-based simulation and discrete-event simulation. Proceedings - Winter Simulation Conference, 135-150.
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  Abstract: This tutorial demonstrates the use of agent-based simulation (ABS) in modeling emergent behaviors. We first introduce key concepts of ABS by using two simple examples: the Game of Life and the Boids models. We illustrate agent-based modeling issues and simulation of emergent behaviors by using examples in social networks, auction-type markets, emergency evacuation, crowd behavior under normal situations, biology, material science, chemistry, and archaeology. Finally, we discuss the relationship between ABS and other simulation methodologies and outline some research challenges in ABS. ©2010 IEEE.
• Lee, S., Son, Y., & Jin, J. (2010). An Integrated Human Decision Making Model for Evacuation Scenarios under a BDI Framework. ACM TRANSACTIONS ON MODELING AND COMPUTER SIMULATION, 20(4).
• Lee, S., Son, Y., & Jin, J. (2010). An integrated human decision making model for evacuation scenarios under a BDI framework. ACM Transactions on Modeling and Computer Simulation, 20(4).
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  Abstract: An integrated Belief-Desire-Intention (BDI) modeling framework is proposed for human decision making and planning for evacuation scenarios, whose submodules are based on a Bayesian Belief Network (BBN), Decision-Field-Theory (DFT), and a Probabilistic Depth-First Search (PDFS) technique. A key novelty of the proposed model is its ability to represent both the human decisionmaking and decision-planning functions in a unified framework. To mimic realistic human behaviors, attributes of the BDI framework are reverse-engineered fromhuman-in-the-loop experiments conducted in the Cave Automatic Virtual Environment (CAVE). The proposed modeling framework is demonstrated for a human's evacuation behaviors in response to a terrorist bomb attack. The simulated environment and agents (models of humans) conforming to the proposed BDI framework are implemented in AnyLogic®agent-based simulation software, where each agent calls external Netica BBN software to perform its perceptual processing function and Soar software to perform its real-time planning and decision-execution functions. The constructed simulation has been used to test the impact of several factors (e.g., demographics, number of police officers, information sharing via speakers) on evacuation performance (e.g., average evacuation time, percentage of casualties). © 2010 ACM.
• Celik, N., & Son, Y. (2009). Sequential Monte Carlo-based fidelity selection in Dynamic-data-driven Adaptive Multi-scale Simulations (DDDAMS). Proceedings - Winter Simulation Conference, 2281-2293.
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  Abstract: In DDDAMS paradigm, the fidelity of a complex simulation model adapts to available computational resources by incorporating dynamic data into the executing model, which then steers the measurement process for selective data update. Real-time inferencing for a large-scale system may involve hundreds of sensors for various quantity of interests, which makes it a challenging task considering limited resources. In this work, a Sequential Monte Carlo method (sequential Bayesian inference technique) is proposed and embedded into the simulation to enable its ideal fidelity selection given massive datasets. As dynamic information becomes available, the proposed method makes efficient inferences to determine the sources of abnormality in the system. A parallelization frame is also discussed to further reduce the number of data accesses while maintaining the accuracy of parameter estimates. A prototype DDDAMS involving the proposed algorithm has been successfully implemented for preventive maintenance and part routing scheduling in a semiconductor supply chain. ©2009 IEEE.
• Garg, A. K., Venkateswaran, J., & Son, Y. -. (2009). Generic interface specifications for integrating distributed discrete-event simulation models. Journal of Simulation, 3(2), 114-128.
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  Abstract: Distributed simulation refers to the technology and methodology that enable interactive execution of multiple simulation models that are geographically distributed and connected via network. While existing standards (eg High Level Architecture) provide a technical architecture to enable distributed simulation, they do not provide any standard pattern for interfacing distributed discrete-event simulation models. In this paper, generic interface specifications have been proposed to enable interoperability among distributed discrete-event simulation models. The interface specification models have been broadly classified into four types: Entity transfer, Data exchange, Resource sharing, and Event notification. The specifications define the minimum set of messages required to realize a situation. The specifications are described in detail using Unified Modelling Language sequence diagrams. A prototype distributed simulation, developed using a commercial-off-the-shelf simulation package, is used to demonstrate the proposed specifications. Finally, to test the validity of the proposed specifications, statistical results obtained from the constructed distributed simulation are compared against those from a single (non-distributed) simulation.
• Lee, S., Celik, N., & Son, Y. (2009). An integrated simulation modelling framework for decision aids in enterprise software development process. International Journal of Simulation and Process Modelling, 5(1), 62-76.
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  Abstract: Development of enterprise software systems requires the collaboration of many stakeholders that form a complex social network. The goal of this paper is to propose a novel simulation modelling framework, which will allow the stakeholders to perform what-if analyses before making their decisions. The proposed framework involves four different modelling paradigms, including Bayesian belief network, Belief-Desire-Intention mimicking a human decision, game-theory mimicking interactions of humans with conflicting goals, and system dynamics for an overall software development. The proposed framework is illustrated with a real case study in Kuali, which is an open source project currently under development by nine universities. Copyright © 2009, Inderscience Publishers.
• Mazhari, E. M., Zhao, J., Celik, N., Lee, S., Son, Y., & Head, L. (2009). Hybrid simulation and optimization-based capacity planner for integrated photovoltaic generation with storage units. Proceedings - Winter Simulation Conference, 1511-1522.
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  Abstract: Unlike fossil-fueled generation, solar energy resources are geographically distributed and highly intermittent, which makes their direct control difficult and requires storage units. The goal of this research is to develop a flexible capacity planning tool, which will allow us to obtain a most economical mixture of capacities from solar generation as well as storage while meeting reliability requirements against fluctuating demand and weather conditions. The tool is based on hybrid (system dynamics and agent-based models) simulation and meta-heuristic optimization. In particular, the proposed tool has been developed for scenarios, where photovoltaic generators and storage units (compressed-air-energy-storage and super-capacitors) are used to supply energy demands in a region characterized by different house-holds considering different times and seasons. The constructed tool has been used to test impact of several factors (e.g. demand growth, efficiencies in PV panel and storage techniques) on the total cost of the system. Initial results look quite promising. ©2009 IEEE.
• Venkateswaran, J., & Son, Y. (2009). Robust supply-chain planning using multi-resolution hybrid models: Experimental study. International Journal of Modelling and Simulation, 29(4), 417-427.
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  Abstract: Today, there is little understanding of how decisions and disturbances at individual members impact the global performance and robustness of a supply chain. The goal of our research has been to analyse the interactions between the planning decisions that are spread across different members of the supply chain, considering the operational aspects at each member as well as the robustness of the plan. To this end, we had proposed a conceptual framework earlier, which involve a multi-scale federation of interwoven simulations and decision models to support integrated analysis of stability and performance in hierarchical supply chain planning. In this paper, it is further developed, fully implemented, and demonstrated via extensive experiments involving a realistic three-echelon conjoined supply chain system. A high level architecture (HLA) is used to integrate the distributed decision and simulation models. For the considered supply chains, various hybrid models have been successfully developed conforming to the framework, and experimental results revealed the advantage of our framework in robust supply chain planning.
• Agrawal, S., Dashora, Y., Tiwari, M. K., & Son, Y. (2008). Interactive particle swarm: A Pareto-adaptive metaheuristic to multiobjective optimization. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, 38(2), 258-277.
• Agrawal, S., Dashora, Y., Tiwari, M., & Son, Y. (2008). Interactive particle swarm: A Pareto-adaptive metaheuristic to multiobjective optimization. IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans, 38(2), 258-277.
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  Abstract: This paper proposes an interactive particle-swarm metaheuristic for multiobjective optimization (MOO) that seeks to encapsulate the positive aspects of the widely used approaches, namely, Pareto dominance and interactive decision making in its solution mechanism. Pareto dominance is adopted as the criterion to evaluate the particles found along the search process. Nondominated particles are stored in an external repository which updates continuously through the adaptive-grid mechanism proposed. The approach is further strengthened by the incorporation of a self-adaptive mutation operator. A decision maker (DM) is provided with the knowledge of an approximate Pareto optimal front, and his/her preference articulations are used to derive a utility function intended to calculate the utility of the existing and upcoming solutions. The incubation of particle-swarm mechanism for the MOO by incorporating an adaptive-grid mechanism, a self-adaptive mutation operator, and a novel decision-making strategy makes it a novel and efficient approach. Simulation results on various test functions indicate that the proposed metaheuristic identifies not only the best preferred solution with a greater accuracy but also presents a uniformly diverse high utility Pareto front without putting excessive cognitive load on the DM. The practical relevance of the proposed strategy is very high in the cases that involve the simultaneous use of decision making and availability of highly favored alternatives. © 2008 IEEE.
• Kim, C., Son, Y. -., Kim, T., & Kim, K. (2008). A virtual enterprise design method based on business process simulation. International Journal of Computer Integrated Manufacturing, 21(7), 857-868.
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  Abstract: In order for a virtual enterprise (VE) to be successful, effective synchronisation of processes between the member enterprises is a major challenge. To overcome this challenge, it is important to select appropriate member enterprises at the establishment phase of a VE that can cope with the business goal and constraints. In this paper, we propose a simulation-based method to evaluate and select proper candidate enterprises from a repository. A broker enterprise after designing a business process provides corresponding business requirements (abstract) to the candidates in the repository, and those candidate enterprises that meet the business requirements respond to the broker. The broker enterprise then simulates the business process (global simulation) considering global performance of the VE, whose results become detailed requirements for the candidate enterprises. The participating enterprises adjust their business conditions using their local simulation to cope with the business constraints. If the candidate enterprise cannot cope with the business constraints, a new candidate is selected from the repository, and the business process is simulated again. This procedure continues until an appropriate candidate is identified, and a virtual enterprise is then established. To support the proposed VE design process, OMG's Model Driven Architecture and the web services technology are employed. Finally, the proposed methods are conceptually illustrated for an exemplary VE.
• Koyuncu, N., Lee, S., Sarfare, P., & Son, Y. (2008). Dynamic-data-driven adaptive multi-scale simulation (DDDAMS) for planning and control of distributed manufacturing enterprises. IIE Annual Conference and Expo 2008, 1611-1616.
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  Abstract: Dynamic-Data-Driven Adaptive Multi-Scale Simulation (DDDAMS) is proposed to adaptively adjust the fidelity of a simulation model against available computational resources by incorporating dynamic data into the executing model, which then steers the measurement process for selective date update. Four algorithms are embedded into a real-time simulator for its DDDAMS capability, including data filtering algorithm, fidelity selection algorithm, fidelity assignment algorithm, and task generation algorithm. Grid computing and Web Services are used for computational resource management and inter-operable communications among distributed software components. The proposed DDDAMS is applied for operational scheduling and preventive maintenance scheduling in a semiconductor manufacturing supply chain.
• Lee, S., & Son, Y. (2008). Integrated human decision making model under belief-desire-intention framework for crowd simulation. Proceedings - Winter Simulation Conference, 886-894.
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  Abstract: An integrated Belief-Desire-Intention (BDI) modeling framework is proposed for human decision making and planning, whose sub-modules are based on Bayesian belief network (BBN), Decision-Field-Theory (DFT), and probabilistic depth first search (PDFS) technique. To mimic realistic human behaviors, attributes of the BDI framework are reverse-engineered from the human-in-the-loop experiments conducted in the Cave Automatic Virtual Environment (CAVE). The proposed modeling framework is demonstrated for human's evacuation behaviors under a terrorist bomb attack situation. The simulated environment and agents (human model) conforming to the proposed BDI framework are implemented in AnyLogic® agentbased simulation software, where each agent calls external Netica BBN software to perform its perceptual processing function and Soar software to perform its real-time planning and decision-execution functions. The constructed simulation has been used to test impact of several factors (e.g. demographics of people, number of policemen) on evacuation performance (e.g. average evacuation time, percentage of casualties). © 2008 IEEE.
• Lee, S., Son, Y., & Jin, J. (2008). Decision field theory extensions for behavior modeling in dynamic environment using Bayesian belief network. INFORMATION SCIENCES, 178(10), 2297-2314.
• Lee, S., Son, Y., & Jin, J. (2008). Decision field theory extensions for behavior modeling in dynamic environment using Bayesian belief network. Information Sciences, 178(10), 2297-2314.
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  Abstract: Decision field theory (DFT), widely known in the field of mathematical psychology, provides a mathematical model for the evolution of the preferences among options of a human decision-maker. The evolution is based on the subjective evaluation for the options and his/her attention on an attribute (interest). In this paper, we extend DFT to cope with the dynamically changing environment. The proposed extended DFT (EDFT) updates the subjective evaluation for the options and the attention on the attribute, where Bayesian belief network (BBN) is employed to infer these updates under the dynamic environment. Four important theorems are derived regarding the extension, which enhance the usability of EDFT by providing the minimum time steps required to obtain the stabilized results before running the simulation (under certain assumptions). A human-in-the-loop experiment is conducted for the virtual stock market to illustrate and validate the proposed EDFT. The preliminary result is quite promising. © 2008 Elsevier Inc. All rights reserved.
• Lee, S., Zhao, X., Shendarkar, A., Vasudevan, K., & Son, Y. (2008). Fully dynamic epoch time synchronisation method for distributed supply chain simulation. International Journal of Computer Applications in Technology, 31(3-4), 249-262.
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  Abstract: A dynamic epoch time synchronisation method for distributed simulation federates is presented. The proposed approach allows federates to advance their local times at full speed to the global safe point, which is dynamically estimated using the look-ahead function for each federate. The simulation then slows for an interaction between federates. This approach aims to reduce the number of time synchronisation occurrences and duration of the conservative phase. The distributed simulation is implemented using the web services technology. The experimental results reveal that the proposed approach reduces simulation execution time significantly while maintaining complete accuracy as compared with two existing methods. Copyright © 2008 Inderscience Enterprises Ltd.
• Seung, H. L., & Son, Y. (2008). Integrated human decision behavior modeling using extended decision field theory and soar under BDI framework. IIE Annual Conference and Expo 2008, 1617-1622.
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  Abstract: An integrated Belief-Desire-Intention framework is proposed for the human decision behavior modeling, which involves extended Decision-Field-Theory, Bayesian belief network, and Soar. To demonstrate the proposed framework, crowd evacuation behaviors under the terrorist bomb attack are considered. Three particular scenarios are bomb explosion, bomb threatening, and threatening after explosion. For each scenario, various agent behaviors are characterized based on familiarity with the area, risk-taking behavior, confidence index, and guidance by police. The environment and agents are implemented in AnyLogic® agent-based simulation software, where Netica® and Soar® are called to perform perceptual processing, real-time planning, and decision-execution in a distributed computing environment.
• Shendarkar, A., Vasudevan, K., Lee, S., & Son, Y. (2008). Crowd simulation for emergency response using BDI agents based on immersive virtual reality. SIMULATION MODELLING PRACTICE AND THEORY, 16(9), 1415-1429.
• Shendarkar, A., Vasudevan, K., Lee, S., & Son, Y. (2008). Crowd simulation for emergency response using BDI agents based on immersive virtual reality. Simulation Modelling Practice and Theory, 16(9), 1415-1429.
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  Abstract: This paper presents a novel methodology involving a Virtual Reality (VR)-based Belief, Desire, and Intention (BDI) software agent to construct crowd simulation and demonstrates the use of the same for crowd evacuation management under terrorist bomb attacks in public areas. The proposed BDI agent framework allows modeling of human behavior with a high degree of fidelity. The realistic attributes that govern the BDI characteristics of the agent are reverse-engineered by conducting human-in-the-loop experiments in the VR-based Cave Automatic Virtual Environment (CAVE). To enhance generality and interoperability of the proposed crowd simulation modeling scheme, input data models have been developed to define environment attributes (e.g., maps, demographics, evacuation management parameters). The validity of the proposed data models are tested with two different evacuation scenarios. Finally, experiments are conducted to demonstrate the effect of various crowd evacuation management parameters on the key performance indicators in the evacuation scenario such as crowd evacuation rate and densities. The results reveal that constructed simulation can be used as an effective emergency management tool. © 2008 Elsevier B.V. All rights reserved.
• Shukla, S. K., Son, Y. J., & Tiwari, M. K. (2008). Fuzzy-based adaptive sample-sort simulated annealing for resource-constrained project scheduling. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 36(9-10), 982-995.
• Shukla, S. K., Son, Y. J., & Tiwari, M. K. (2008). Fuzzy-based adaptive sample-sort simulated annealing for resource-constrained project scheduling. International Journal of Advanced Manufacturing Technology, 36(9-10), 982-995.
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  Abstract: This paper deals with the resource-constrained project scheduling problems (RCPSP), where the activities of a project have to be scheduled with the objective of minimizing the makespan subject to both temporal and resource constraints. Being one of the most intractable problems in the operations research area, RCPSP has often been a target and test bed for establishing new optimization tools and techniques. In order to efficiently solve this computationally complex problem in real time, we propose a parallel intelligent search technique named the fuzzy-based adaptive sample-sort simulated annealing (FASSA) heuristic. The basic ingredients of the proposed heuristic are the serial schedule generation scheme (SGS), sample-sort simulated annealing (SSA), and the fuzzy logic controller (FLC). The serial SGS generates the initial schedules following both the precedence and resource constraints. SSA is basically a serial simulated annealing algorithm, artificially extended across an array of samplers operating at statistically monotonically increasing temperatures. The FLC makes the SSA adaptive in nature by regulating the swapping rate of an activity's priority during an improved schedule generation process. The implementation results of the FASSA heuristic over extremely hard test bed, adopted from the Project Scheduling Problem Library (PSPLIB), reveal its superiority over most of the currently existing approaches. © 2007 Springer-Verlag London Limited.
• Shukla, S. K., Tiwari, M. K., & Son, Y. J. (2008). Bidding-based multi-agent system for integrated process planning and scheduling: A data-mining and hybrid tabu-SA algorithm-oriented approach. International Journal of Advanced Manufacturing Technology, 38(1-2), 163-175.
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  Abstract: This paper conceptualizes a bidding-based multi-agent system for solving integrated process-planning and scheduling problem. The proposed architecture consists of various autonomous agents capable of communicating (bidding) with each other and making decisions based on their knowledge. Moreover, in contrast to the traditional model of integrated process-planning and scheduling problem, a new paradigm has been conceptualized by considering tool cost as a dynamic quantity rather than a constant. Tool cost is assumed to comprise tool-using cost and its repairing cost. The repairing cost is considered to depend on the tool-breaking probability, which is predicted by the data-mining agent equipped with the virtues of C-fuzzy decision tree. When a job arrives at the shop floor, the component agent announces a bid for one feature at a time to all the machine agents. Among the machine agents capable of producing the first feature, one comes forward to become a "leader", and groups other machine agents for the processing of remaining features of the job. Once all features are assigned to the appropriate machines, the leader then sends this allocation information to the optimization agent. The optimization agent finds optimal/near-optimal process plans and schedules via the hybrid tabu-SA algorithm. © 2007 Springer-Verlag London Limited.
• Shukla, S. K., Tiwari, M. K., & Son, Y. J. (2008). Bidding-based multi-agent system for integrated process planning and scheduling: a data-mining and hybrid tabu-SA algorithm-oriented approach. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 38(1-2), 163-175.
• Zhao, X., & Son, Y. -. (2008). Extended BDI framework for modelling human decision-making in complex automated manufacturing systems. International Journal of Modelling and Simulation, 28(3), 347-356.
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  Abstract: This paper presents a novel software agent model to replace the partial decision-making function of a human. The proposed model, employing the belief, desire, intention (BDI) agent framework, is capable of (1) generating plans in real time, (2) supporting both the reactive and the proactive decision-making, (3) maintaining situation awareness in human language such as logic, and (4) changing the commitment strategy adaptive to historical performance. In this paper, the proposed model has been developed in the context of the human operator who is responsible for error detection and recovery in a complex automated manufacturing system. A distributed computing platform has been used to integrate an agent (implemented in JACK), real human, and the environment (Arena simulation software).
• Anjos, D. C., Cohens, D., Hansen, C., Koyuncu, N., Lee, S., Shendarkar, A., Vasudevan, K. K., & Son, Y. (2007). DDDAS-based multi-fidelity simulation for online preventive maintenance scheduling in semiconductor supply chain. IIE Annual Conference and Expo 2007 - Industrial Engineering's Critical Role in a Flat World - Conference Proceedings, 110-115.
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  Abstract: This research intends to augment the validity of simulation models in the most economic way via incorporating dynamic data into the executing model, which then steers the measurement process for selective data update. To this end, we developed four algorithms that are embedded into the simulations, including 1) data filtering algorithm utilizing control charts, 2) preliminary fidelity selection algorithm using the Bayesian belief network, 3) fidelity assignment algorithm considering the currently available computational resources and integer programming, and 4) real-time scheduling algorithm using multi-linear regression. A prototype system was successfully developed for preventive maintenance scheduling for a semiconductor supply chain.
• Koyuncu, N., Lee, S., Vasudevan, K. K., Son, Y., & Sarfare, P. (2007). DDDAS-based multi-fidelity simulation for online preventive maintenance scheduling in semiconductor supply chain. Proceedings - Winter Simulation Conference, 1915-1923.
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  Abstract: This research intends to augment the validity of simulation models in the most economic way using the DDDAS (Dynamic Data Driven Application Systems) paradigm. Implementation of DDDAS requires automated switching of model fidelity and incorporating selective, dynamic data into the executing simulation model. Comprehensive system architecture and methodologies are proposed, where the components include 1) RT (Real Time) DDDAS simulation, 2) grid computing modules, 3) Web Service communication server, 4) database, 5) various sensors, and 6) real system. Four algorithms are developed to facilitate integration of the various components in the DDDAS system. They are 1) data filtering algorithm using control charts, 2) preliminary fidelity selection algorithm using Bayesian belief network, 3) fidelity assignment algorithm using integer programming and 4) simulation model reconstruction algorithm using multiple linear regression. A prototype DDDAS simulation was successfully implemented for preventive maintenance scheduling in a semiconductor supply chain. The initial results look quite promising. © 2007 IEEE.
• Lee, S., Son, Y., & Wysk, R. A. (2007). Simulation-based planning and control: From shop floor to top floor. JOURNAL OF MANUFACTURING SYSTEMS, 26(2), 85-98.
• Lee, S., Son, Y., & Wysk, R. A. (2007). Simulation-based planning and control: From shop floor to top floor. Journal of Manufacturing Systems, 26(2), 85-98.
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  Abstract: This paper illustrates how simulation-based shop-floor planning and control can be extended to enterprise-level activities (top floor). First, the general planning and control concept are discussed, followed by an overview of simulation-based shop-floor planning and control. Analogies between the shop floor and top floor are discussed in terms of the components required to construct simulation-based planning and control systems. Analogies are developed for resource models, coordination models, physical entities, and simulation models. Differences between the shop floor and top floor are also discussed in order to identify new challenges faced for top-floor planning and control. A major difference between the top floor and the shop floor is the way a simulation model is constructed for use in planning, depending on whether time synchronization among member simulations becomes an issue or not. Another difference is in the distributed communication/computing platform. This work uses a distributed computing platform using Web services technology to integrate heterogeneous simulations and systems in a distributed top-floor control environment. The research results reveal that simulation-based planning and control is extensible to the top-floor environment's evolving new research challenges. © 2008 The Society of Manufacturing Engineers.
• Min, H. J., Beyeler, W., Brown, T., Son, Y. J., & Jones, A. T. (2007). Toward modeling and simulation of critical national infrastructure interdependencies. IIE TRANSACTIONS, 39(1), 57-71.
• Min, H. J., Beyeler, W., Brown, T., Son, Y. J., & Jones, A. T. (2007). Toward modeling and simulation of critical national infrastructure interdependencies. IIE Transactions (Institute of Industrial Engineers), 39(1), 57-71.
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  Abstract: Modern society's physical health depends vitally upon a number of real, interdependent, critical infrastructure networks that deliver power, petroleum, natural gas, water, and communications. Its economic health depends on a number of other infrastructure networks, some virtual and some real, that link residences, industries, commercial sectors, and transportation sectors. The continued prosperity and national security of the US depends on our ability to understand the vulnerabilities of and analyze the performance of both the individual infrastructures and the entire interconnected system of infrastructures. Only then can we respond to potential disruptions in a timely and effective manner. Collaborative efforts among Sandia, other government agencies, private industry, and academia have resulted in realistic models for many of the individual component infrastructures. In this paper, we propose an innovative modeling and analysis framework to study the entire system of physical and economic infrastructures. That framework uses the existing individual models together with system dynamics, functional models, and nonlinear optimization algorithms. We describe this framework and demonstrate its potential use to analyze, and propose a response for, a hypothetical disruption.
• Smith, E. D., Son, Y. J., Piattelli-Palmarini, M., & Bahill, A. T. (2007). Ameliorating mental mistakes in tradeoff studies. SYSTEMS ENGINEERING, 10(3), 222-240.
• Smith, E. D., Young, J. S., Plattelli-Palmarinl, M., & Bahill, A. T. (2007). Ameliorating mental mistakes in tradeoff studies. Systems Engineering, 10(3), 222-240.
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  Abstract: Tradeoff studies are broadly recognized and mandated as the method for simultaneously considering multiple alternatives with many criteria, and as such are recommended in the Capability Maturity Model Integration (CMMI) Decision Analysis and Resolution (DAR) process. Tradeoff studies, which involve human numerical judgment, calibration, and data updating, are often approached with under confidence by analysts and are often distrusted by decision makers. The decision-making fields of Judgment and Decision Making, Cognitive Science and Experimental Economics have built up a large body of research on human biases and errors in considering numerical and criteria-based choices. Relationships between experiments in these fields and the elements of tradeoff studies show that tradeoff studies are susceptible to human mental mistakes: This paper indicates ways to eliminate the presence, or ameliorate the effects of mental mistakes on tradeoff studies. © 2007 Wiley Periodicals, Inc.
• Son, Y., & Venkateswaran, J. (2007). Hierarchical supply chain planning architecture for integrated analysis of stability and performance. International Journal of Simulation and Process Modelling, 3(3), 153-169.
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  Abstract: In this paper, a novel architecture that allows a multi-scale federation of interwoven simulations and decision models to support integrated analysis of stability and performance in hierarchical production planning for supply chain networks is proposed. The proposed scheme is divided into four stages: plan stability analysis, plan optimisation, schedule optimisation and concurrent decision evaluation. The plans are more robust against future disturbances and more feasible for implementation than those from the conventional methods. Detailed functional and process models of the proposed system are specified using formal IDEF tools. The proposed approach is demonstrated using a realistic three-echelon supply chain system. © 2007, Inderscience Publishers.
• Son, Y., Wysk, R. A., Bayraksan, G., & Lin, W. (2007). IIE Annual Conference and Expo 2007 - Industrial Engineering's Critical Role in a Flat World - Conference Proceedings: Preface. IIE Annual Conference and Expo 2007 - Industrial Engineering's Critical Role in a Flat World - Conference Proceedings.
• Venkateswaran, J., & Son, Y. (2007). Effect of information update frequency on the stability of production-inventory control systems. INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 106(1), 171-190.
• Venkateswaran, J., & Son, Y. (2007). Effect of information update frequency on the stability of production-inventory control systems. International Journal of Production Economics, 106(1), 171-190.
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  Abstract: Production ordering and inventory dynamics in a manufacturing system are analyzed using function transformation techniques (z-transform) and their conditions for stability are examined. A generic model which captures the mixing and variability in the production process is developed. Variation in the stability of the system operating under sufficient inventory coverage and under limited inventory coverage is highlighted. The effects of the frequency of information update on stability are then examined by relating the update frequency to the sampling interval of the underlying difference equations. System dynamics simulations are used to demonstrate the stable or unstable behaviour of the production-inventory system. © 2006 Elsevier B.V. All rights reserved.
• Zhao, X., & Son, Y. (2007). Penalty function-based two-level hybrid shop floor control system. IEEE Transactions on Automation Science and Engineering, 4(2), 220-232.
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  Abstract: Although several hybrid shop floor control architectures have been proposed in the literature, varying degrees of autonomy of subordinate controllers and their effects on supervisory level performance have not been studied. In this paper, we present a new hybrid control architecture with two levels, where the autonomy of subordinate agents changes adaptively. The penalty function in the architecture represents the degree of negative impact on performance that will result from changing the original schedule. When a disturbance occurs, the disturbance agent invokes rescheduling at the appropriate level depending on the threshold disturbance level. The subordinate agents execute tasks based on the schedule from the supervisory agent in the absence of disturbances; or else revise the original schedule optimally with regard to the supervisory level performance (via penalty function) and the disturbance before executing the tasks. We present math programming formulations, quantitative metrics to indicate the disturbance level and the levels of autonomy. The proposed architecture is illustrated using a job shop problem and is then tested with various other problems. Note to Practitioners - In a hybrid shop floor control system, the objective of global system performance conflicts with the objective of a timely response to local disturbances. For a given disturbance, there is a need to compare the cost (e.g., computation time) associated with supervisory level rescheduling against the potential improvement in system performance that this rescheduling can provide. If the cost of rescheduling is higher, rescheduling at the subordinate level will be appropriate. Otherwise, rescheduling at the supervisory level will be appropriate. In this paper, manufacturing scheduling problems of various complexities are used to discuss the tradeoff between the objectives listed above. We then use these problems to show how to find an appropriate threshold value to trigger subordinate or supervisory level rescheduling. Limited classes of performance metrics are considered. Work is currently being carried out to extend the approach to broader performance metrics. It is believed that our results can be applied to other systems for which hierarchical structures are commonly used. Examples of such systems exist in the transportation, health-care, and defense sectors. © 2007 IEEE.
• Cho, H., Son, Y. J., & Jones, A. (2006). Design and conceptual development of shop-floor controllers through the manipulation of process plans. International Journal of Computer Integrated Manufacturing, 19(4), 359-376.
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  Abstract: A shop-floor control system (SFCS) performs the decision-making and execution functions necessary to fill production orders efficiently. To cope with a variety of dynamic factors, the SFCS must be able to perform these functions in real time. This paper proposes a way to reduce the cost of developing the software that implements this real-time requirement. It describes a design and development framework that uses hierarchical process plans and simulation. The plans are written in the process specification language (PSL) developed at the National Institute for Standards and Technology (NIST) and coded as extensible markup language (XML) document type definitions (DTDs). The decision maker in each controller parses these DTDs into a non-linear graph, resolves the AND-junctions and OR-junctions, determines a sequence of production tasks and generates the set of messages to execute those tasks. The decision planner, when called by the decision maker, evaluates several sets of control rules using a corresponding simulation model, chooses the most promising set and provides it to the decision maker. The proposed concept enables control software to be designed and developed in terms of the evolution of process plans, so both the decision maker and the executor can be generic and the simulation model (decision planner) can be generated in an automatic manner. The generality and validity of the proposed concept has been conceptually tested for diverse manufacturing systems generated from a designed experiment.
• Kim, C. -., Son, Y. -., Kim, T. -., Kim, K., & Baik, K. (2006). A modeling approach for designing a value chain of virtual enterprise. International Journal of Advanced Manufacturing Technology, 28(9), 1025-1030.
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  Abstract: As the advent of digital economy changes business environment dramatically, virtual enterprise (VE), in general the interactions among business partners in a value chain, has become a key factor to survive under the competitive business environment. VE reveals that more complex and dynamic business processes should be considered as assembled service components in order to integrate the collaborative business processes. Therefore, a formal standard schema for describing and managing the business processes is required. In this paper, we propose a consistent modeling approach that combines enterprise modeling and simulation modeling to design a value chain of a VE. This methodology will provide designers with insight into the business processes of a VE and help identify and resolve unpredictable bottlenecks on the execution of virtual business processes. This paper also illustrates an implemented modeling tool which is based on the generalized model suggested by the working group of the international conference on enterprise integration and modeling technology (ICEIMT) and notations by the object management group (OMG)'s unified modeling language (UML) profile for enterprise distributed object computing (EDOC). © Springer-Verlag 2006.
• Lee, S., Zhao, X., Shendarkar, A., Vasudevan, K., & Son, Y. (2006). Epoch time synchronization method with continuous update for distributed simulation. IFAC Proceedings Volumes (IFAC-PapersOnline), 12(PART 1).
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  Abstract: A new time synchronization method for distributed simulations is proposed. In this approach, each federate estimates its potential synchronization point (PSP)). The coordinator, after receiving PSPs, selects the minimum of them (synchronization point (SP)). Each federate then advances its time to SP. While each federates advances its time, it re-calculates its PSP whenever the certain system status changes, and sends it to the coordinator. The coordinator updates SP when the updated PSPs affect it, and notifies its new SP to the federates. When a federate reaches close to the actual epoch event, the synchronization method switches to the conservative phase. Copyright © 2006 IFAC.
• Shendarkar, A., Vasudevan, K., Lee, S., & Son, Y. (2006). Crowd simulation for emergency response using BDI agent based on virtual reality. PROCEEDINGS OF THE 2006 WINTER SIMULATION CONFERENCE, VOLS 1-5, 545-+.
• Shendarkar, A., Vasudevan, K., Lee, S., & Son, Y. (2006). Crowd simulation for emergency response using bdi agent based on virtual reality. Proceedings - Winter Simulation Conference, 545-553.
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  Abstract: This paper presents a novel VR (Virtual Reality) trained BDI (belief, desire, intention) software agent used to construct crowd simulations for emergency response. The BDI framework allows modeling of human behavior with a high degree of fidelity. The proposed simulation has been developed using AnyLogic software to mimic crowd evacuation from an area under a terrorist bomb attack. The attributes that govern the BDI characteristics of the agent are studied by conducting human in the loop experiments in VR using the CAVE (Cave Automatic Virtual Environment). To enhance generality and interoperability of the proposed crowd simulation modeling scheme, input data models have been developed to define environment attributes. Experiments are also conducted to demonstrate the effect of various parameters on key performance indicators such as crowd evacuation rate and densities. © 2006 IEEE.
• Venkateswaran, J., & Son, Y. (2006). Effects of information synchronization frequency on the stability of supply chains. 2006 IIE Annual Conference and Exhibition.
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  Abstract: With modern supply chains hurtling towards 'information overloading,' it is of great interest to know what data is required for effective decision making and how often the data needs to be updated. The latter part on how often is the focus of this paper. The inventory and production ordering policies among the players (Manufacturer and Distributors) of a two echelon supply chain are studied. System dynamics models of the different players are developed. Z-transform techniques are employed to derive the general stability condition. Stability of the supply chain under different strategies (communicative vs. vendor managed inventory) is appraised and their implications on the information synchronization needs are analyzed.
• Madan, M., Son, Y., Cho, H., & Kulvatunyou, B. (2005). Determination of efficient simulation model fidelity for flexible manufacturing systems. International Journal of Computer Integrated Manufacturing, 18(2-3), 236-250.
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  Abstract: This paper presents a framework for the determination of an efficient level of simulation model fidelity for flexible manufacturing systems, which will achieve acceptable output accuracy with minimum resources and thereby reduce model building effort and computation time. To this end, we first formally define different levels of model fidelity using building blocks available in object-oriented (O-O) modelling, where an operation at a higher level is either decomposed into more detailed operations or subjected to more constraints at a lower level. In this paper, five models with different fidelities are defined. Then, simulation models that conform to these O-O models are constructed. Using these simulation models, intensive experiments are conducted to examine how the factors that characterize an FMS contribute to the relative errors of outputs from different models. Since no actual systems are considered, the results generated from the most detailed simulation model are used as references. The experimental results are then summarized by regression-based meta-models. In the proposed framework, the most efficient model for a new FMS is identified so that the relative error of a model estimated from the meta-model is closest to the threshold value provided by users. This framework is tested by two sample FMSs, and the initial results look quite promising. © 2005 Taylor & Francis Ltd.
• Madhusudan, T., & Son, Y. (2005). A simulation-based approach for dynamic process management at web service platforms. Computers and Industrial Engineering, 49(2), 287-317.
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  Abstract: Web services technology is being adopted as a viable deployment approach for future distributed software systems that enable business-to-business and business-to-consumer interactions across the open and dynamic internet environment. Recent research is focused on developing support technologies for web service discovery, on-demand service composition, and robust execution to facilitate web services based deployment of business processes. Developing techniques to cope with the volatile and open nature of the web during execution of composite services at the service platform is essential for delivering reliable and acceptable performance in this new process delivery framework. In this paper, we propose a simulation-based framework to guide scheduling of composite service execution. Online simulation of the dynamics of the open environment is used for scheduling service requests at the service platform. Comparison of the look-ahead simulation for different scheduling policies with the current execution state provides guidelines for service execution in order to cope with system volatility. We have implemented a prototype of the proposed framework and illustrate the feasibility of our approach with experimental studies. © 2005 Elsevier Ltd. All rights reserved.
• Rathore, A., Balaraman, B., Zhao, X., Baek, S. H., Venkateswaran, J., Son, Y., & Wysk, R. A. (2005). Development and benchmarking of an epoch time synchronization method for distributed simulation. IIE Annual Conference and Exposition 2005.
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  Abstract: In this work, a new epoch time synchronization approach for distributed simulation federates is proposed. The approach allows federates to advance their local times at full speed to the minimum of the estimated next epoch event times, which are calculated by a recursive look-ahead function at each federate. A client/server infrastructure is also presented for distributed simulation. The proposed approach and infrastructure are demonstrated using a manufacturing supply chain simulation composed of five distributed federates. The experimental results reveal the proposed approach improves supply chain simulation execution time significantly while maintaining complete accuracy as compared with the conservative synchronization approaches.
• Rathore, A., Balaraman, B., Zhao, X., Venkateswaran, J., Son, Y., & Wysk, R. A. (2005). Development and benchmarking of an epoch time synchronization method for distributed simulation. JOURNAL OF MANUFACTURING SYSTEMS, 24(2), 69-78.
• Rathore, A., Balaraman, B., Zhao, X., Venkateswaran, J., Son, Y., & Wysk, R. A. (2005). Development and benchmarking of an epoch time synchronization method for distributed simulation. Journal of Manufacturing Systems, 24(2), 69-78.
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  Abstract: In this paper, a new epoch time synchronization approach for distributed simulation federates is presented. The approach allows federates in the simulation system to advance their local times at full speed while it is safe to do so. That is, the simulation moves rapidly to the minimum next epoch (interaction) event time, which is calculated using the minimum sojourn time for each federate, and then slows for federation synchronization. The proposed approach is demonstrated using a manufacturing supply chain simulation composed of four distributed federates. Experiments are executed to benchmark the proposed epoch time synchronization method against conventional conservative synchronization methods to show typical improvements for simulation operation. The experimental results reveal that the proposed approach reduces supply chain simulation execution time significantly while maintaining complete accuracy as compared with traditional conservative federation coordination approaches. © 2006 Society of Manufacturing Engineers.
• Son, Y. (2005). Distributed simulation for multi-university collaborative manufacturing. Technical Paper - Society of Manufacturing Engineers, TP05PUB223.
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  Abstract: In today's competitive business environment, companies design, manufacture and distribute products through a global supply chain network in pursuit of lower cost, shorter time-to-market and better quality. This new trend has generated critical competency gaps between today's global manufacturing workforce needs and what is provided by the current engineering curriculum. To respond to this need, our long-term goal is to enhance the experiences of undergraduate students in the entire product realization process under a global supply chain environment to prepare them for the challenges they will face when leaving the university. The objective of this paper (short-term goal) is to present a modeling and simulation platform, which will support rapid fabrication of supply chains by defining the facility set, their capability and decision models, product structure and the natural environment. The platform will help students under a multi-university supply chain understand supply chain behavior with a realistic supply chain model.
• Son, Y., Kulvatunyou, B., Cho, H., & Feng, S. (2005). A semantic web service and simulation framework to intelligent distributed manufacturing. American Society of Mechanical Engineers, Manufacturing Engineering Division, MED, 16-2, 1473-1474.
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  Abstract: To cope with today's fluctuating markets, a virtual enterprise (VE) concept can be employed to achieve the cooperation among independently operating enterprises. The success of VE depends on reliable interoperation among trading partners. This paper describes a framework based on semantic web of manufacturing and simulation services to enable business and engineering collaborations between VE partners, particularly a design house and manufacturing suppliers. To this end, we first give an overview of distributed manufacturing in the web service framework, including detailed activity and information flow diagrams. Second, we propose an ontological definition of resource models and process-capability models using an ontology definition language. Third, we propose a method based on stochastic discrete-event simulation, whose model is automatically generated from the resource and process models, to evaluate highly nonlinear process plans. Finally, we present a prototype system to demonstrate an interoperable collaboration using semantic webs. Copyright © 2005 by ASME.
• Venkateswaran, J., & Son, Y. (2005). Information synchronization effects on the stability of collaborative supply chain. Proceedings - Winter Simulation Conference, 2005, 1668-1676.
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  Abstract: In this paper, the dynamics of a collaborative supply chain have been analyzed using transform techniques. The general conditions for stability of the supply chains are derived and the effects of inter-player sampling intervals are analyzed. System dynamics simulation models of the different members of the supply chain are developed. Z-transform techniques are employed to derive the general stability conditions (settings of control parameters that produce stable response). The variation in the supply chain's stability in response to the information synchronization frequency is examined by relating the update frequency to the sampling interval of the underlying difference equations. Existence of instability due to improper parameter selection and improper sampling interval selection is thus confirmed, and guidance for the selection of appropriate parameters to guarantee system stability is presented. Simulations are used to confirm our analysis and help demonstrate the stable or unstable behavior of the supply chain.
• Venkateswaran, J., & Son, Y. -. (2005). Hybrid system dynamic - Discrete event simulation-based architecture for hierarchical production planning. International Journal of Production Research, 43(20), 4397-4429.
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  Abstract: Multi-plant production planning problem deals with the determination of type and quantity of products to produce at the plants over multiple lime periods. Hierarchical production planning provides a formal bridge between long-term plans and short-term schedules. A hybrid simulation-based hierarchical production planning architecture consisting of system dynamics (SD) components for the enterprise level planning and discrete event simulation (DES) components for the shop-level scheduling is presented. The architecture consists of the Optimizer, Performance Monitor and Simulator modules at each decision level. The Optimizers select the optimal set of control parameters based on the estimated behaviour of the system. The enterprise-level simulator (SD model) and shop-level simulator (DES model) interact with each other to evaluate the plan. Feedback control loops are employed at each level to monitor the performance and update the control parameters. Functional and process models of the proposed architecture are specified using IDEF. The internal mechanisms of the modules are also described. The modules are interfaced using High Level Architecture (HLA). Experimental results from a multi-product multi-facility manufacturing enterprise demonstrate the potential of the proposed approach.
• Venkateswaran, J., Zhao, X., & Son, Y. (2005). Integrated performance and stability analysis for VMI supply chains using multi-resolution hybrid models. IIE Annual Conference and Exposition 2005.
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  Abstract: Performance and stability issues of a supply chain are synthetically considered in this paper. An integrated two-level VMI-HPP architecture consisting of multi-resolution hybrid models is proposed. Techniques to synchronize these hybrid models across different levels are developed. The aggregate level performs planning across the supply chain, where performance and stability issues are concurrently addressed with non-linear optimization and systemdynamics techniques. The detailed level performs scheduling at each chain partner using non-linear optimization and discrete event modeling techniques. The distributed models are integrated under HLA infrastructure. Performance of combined cost and stability analysis is appraised against a method considering only cost.
• Zhao, X., Venkateswaran, J., & Son, Y. (2005). Modeling human operator decision-making in manufacturing systems using BDI agent paradigm. IIE Annual Conference and Exposition 2005.
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  Abstract: Human operators are imperative to the functioning and success of a manufacturing system. Yet there is a noticeable lack of research in modeling of human operators, especially decision-making aspects. In this paper, the complex task of modeling of human operator decision-making in a manufacturing system is addressed using Belief-Desire-Intention (BDI) agent paradigm. The roles, responsibilities and services of the operator are mapped on to mental models of beliefs, desires and intentions. The dynamic evolution of the mental models is also highlighted. The functioning of the human operator model is illustrated by integrating the model with a shop floor control system.
• Venkateswaran, J., & Son, Y. (2004). Design and development of a prototype distributed simulation for evaluation of supply chains. International Journal of Industrial Engineering : Theory Applications and Practice, 11(2), 151-160.
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  Abstract: In this paper, a prototype distributed simulation system is proposed to evaluate viability of a simulated supply chain. Members of a supply chain, activity definitions for each member, and information and material flow among members are discussed. IDEF∅ functional modeling tool has been used to model the functions of the system and the relationships among the functions. The interaction between the members of the system is then illustrated using time-sequence diagrams, and the behavior of each member is represented using the deterministic finite state automata. These formal models have formed the basis for the development of the distributed simulation system. Reusable simulation models for each of the members of the system have been developed using commercial simulation tools such as Arena™ and ProModel™. The High Level Architecture (HLA) Run Time Infrastructure (RTI) has been used to provide an interface to create the distributed simulation system. Preliminary performance tests have been conducted to evaluate the suitability of the proposed system in the Internet environment. Significance: This paper addresses the application of distributed simulation technology to evaluation of potential supply chains. The use of distributed simulation technology allows each potential partner to hide any proprietary information in the implementation of the individual simulation, but still provide enough information to evaluate the supply chain as a whole. © International Journal of Industrial Engineering.
• Venkateswaran, J., & Son, Y. (2004). Distributed and hybrid simulations for manufacturing systems and integrated enterprise. IIE Annual Conference and Exhibition 2004, 177-182.
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  Abstract: Two categories of simulation that have gained prominence in the past decade are discrete event simulation (DES) and system dynamic simulation (SD). DES is used to model a system in detail to comprehend the actual behavior of the individual components. In contrast, SD simulation is used to build models using aggregated data for system wide dynamic flow analysis of managerial decisions. The need for an integrated hybrid simulation environment is highlighted and prototype architecture is presented. An application methodology in the area of hierarchical production planning in a manufacturing enterprise along with a preliminary feasibility analysis is then presented.
• Venkateswaran, J., & Son, Y. J. (2004). Impact of modelling approximations in supply chain analysis - An experimental study. International Journal of Production Research, 42(15), 2971-2992.
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  Abstract: This paper presents a study of the comparison of the quality of results obtained at different levels of detail using a supply chain simulation. Analysis of supply chain is typically carried out using aggregated information to maintain the level of complexity of the simulation model at a manageable level. Advances in simulation have provided the ability to build comprehensive (detailed), modular models. The quantitative effect of detailed modelling on the corresponding analysis is investigated in this paper. A three-echelon supply chain is analysed using simulation models of varying levels of detail. Using each of these models, four sets of intensive experiments are performed. The first experiment intends to test whether the supply chain dynamics themselves depend on the modelling accuracy that represents the supply chain. The second and third experiments are conducted to test whether the effectiveness of the strategies employed to reduce the supply chain dynamics vary depending on the type (different detail) of model representing the supply chain. In the fourth experiment, statistical techniques are employed to identify which modelling aspect has the most influence on the supply chain dynamics. It is found that the approximations used in modelling, such as delays and capacity, have more impact on the outcome of supply chain analysis than end customer demand, Evidence that both the basic problem (supply chain dynamics) and the solution (strategy to reduce the dynamics) are greatly influenced by the modelling accuracy are presented.
• Venkateswaran, J., Son, Y., & Jones, A. (2004). Hierarchical production planning using a hybrid system dynamic-discrete event simulation architecture. Proceedings - Winter Simulation Conference, 2, 1094-1102.
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  Abstract: Hierarchical production planning provides a formal bridge between long-term plans and short-term schedules. A hybrid simulation-based production planning architecture consisting of system dynamics (SD) components at the higher decision level and discrete event simulation (DES) components at the lower decision level is presented. The need for the two types of simulation has been justified. The architecture consists of four modules: Enterprise-level decision maker, SD model of enterprise, Shop-level decision maker and DES model of shop. The decision makers select the optimal set of control parameters based on the estimated behavior of the system. These control parameters are used by the SD and DES models to determine the best plan based on the actual behavior of the system. High Level Architecture has been employed to interface SD and DES simulation models. Experimental results from a single-product manufacturing enterprise demonstrate the validity and scope of the proposed approach.
• Zhao, X., & Son, Y. (2004). Penalty function-based hybrid shop floor control system. IIE Annual Conference and Exhibition 2004, 653-659.
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  Abstract: Varying degrees of autonomy of subordinate agents and their effects to the global performance have not been studied. In this paper, a new hybrid control architecture is proposed with the capability of dynamic update of autonomy of agents. The key feature is the penalty function, which indicates the degree of negative impact of changing the original schedule on the global performance. The penalty function is used by subordinate agents in their quick revision of schedules to react to a disturbance without degrading the global performance. We present math programming formulations, metrics for disturbances and autonomy, and illustration using an example.
• Zhou, M., Son, Y. J., & Chen, Z. (2004). Knowledge representation for conceptual simulation modeling. Proceedings - Winter Simulation Conference, 1, 450-458.
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  Abstract: Simulation is a powerful tool that helps decision makers in business and industry to solve difficult and complex problems, reduce cost, improve quality and productivity, and shorten time-to-market. However the technology is still underutilized in many applications due to several reasons. In this study we address these issues using a knowledge engineering approach, i.e. develop efficient and robust models and formats to capture, represent and organize the knowledge for developing conceptual simulation models that can be generalized and interfaced with different applications and implementation tools. The research fits into a larger project effort that aims to create a sustained research program on knowledge-based simulation.
• Jang, P. Y., Son, Y. J., & Cho, H. (2003). Elaboration and validation of AND/OR graph-based non-linear process plans for shop floor control. International Journal of Production Research, 41(13), 3019-3043.
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  Abstract: Feature-based process planning has been popular in academia and industry owing to its ability rigorously to integrate design and manufacturing. In spite of this benefit, feature-based process planning has been difficult to implement because it is not easy to extract even simple features from the design data automatically and efficiently. Furthermore, it is even more difficult to construct the temporal precedence relationships among the extracted features with regard to plan alternatives and sequence options. The objective here is to present elaboration and validation methodologies for AND/OR graph-based non-linear process plans that help users construct, validate or modify a controller-friendly process plan easily and efficiently. An elaborated process plan created by a CAPP or an experienced process planner should be validated with respect to various validation criteria, such as the shape of a finished part, feature interaction, feature interference, feature manufacturability and flexibility for shop floor control. For each validation criteria, the invalid indicator matrix proposed here can quantify the degree of invalidity of the process plan. The invalid indicator matrix will help the process planner fix and refine rapidly the elaborated process plan. The methodologies proposed will save cost and time in the production of a controller-friendly process plan. Initial results are promising.
• Rabelo, L., Helal, M., Jones, A., Min, J., Son, Y., & Deshmukh, A. (2003). A hybrid approach to manufacturing enterprise simulation. Winter Simulation Conference Proceedings, 2, 1125-1133.
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  Abstract: Manufacturing enterprise decisions can be classified into four groups: business decisions, design decisions, engineering decisions, and production decisions. Numerous physical and software simulation techniques have been used to evaluate specific decisions by predicting their impact on the system as measured by one or more performance measures. In this paper, we focus on production decisions, where discrete-event simulation models perform that evaluation. We argue that such an evaluation is limited in time and scope, and does not capture the potential impact of these decisions on the whole enterprise. We propose integrating these discrete-event models with system dynamic models and we show the potential benefits of such an integration using an example of semiconductor enterprise.
• Ryu, K., Son, Y., & Jung, M. (2003). Framework for fractal-based supply chain management of e-Biz companies. Production Planning and Control, 14(8), 720-733.
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  Abstract: The high degree of uncertainty of customer demand makes it difficult for e-Biz companies to facilitate their profit maximization. The type of e-Biz company focused in this paper is a B2C (business-to-customer) which connects customers with product manufacturers through the Web interface. In this paper, the B2C company interacts with customers, multiple external manufacturers and a single transportation system. To deal with complicated interactions and relationships among customers, manufacturers and a transportation system, a comprehensive management system to support the B2C company is inevitable. This paper proposes a fractal-based framework for the management of e-Biz companies, where each member in the supply chain is modelled with a self-similar structure referred to as a 'fractal'. The basic fractal unit (BFU) consists of five functional modules, including an observer, an analyser, a resolver, an organizer and a reporter. In this paper, functions of each module will be defined with UML (Unified Modelling Language). Then, the analysers and the resolvers (modules associated with decision-making) for each individual fractal will be specified with mathematical models. A profit model for the company-level fractal will then be formulated. Finally, a numerical example for an exemplary e-Biz company functioning B2C will be presented for the illustration of the proposed methodology.
• Ryu, K., Son, Y., & Jung, M. (2003). Modeling and specifications of dynamic agents in fractal manufacturing systems. Computers in Industry, 52(2), 161-182.
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  Abstract: In order to respond to a rapidly changing manufacturing environment and market, manufacturing systems must be flexible, adaptable, and reusable. The fractal manufacturing system (FrMS) is one of the new manufacturing paradigms that address the need for these characteristics. The FrMS is comprised of a number of "basic components", each of which consists of five functional modules: (1) an observer, (2) an analyzer, (3) an organizer, (4) a resolver, and (5) a reporter. Each of these modules, using agent technology, autonomously cooperates and negotiates with others while processing its own jobs. The resulting architecture has a high degree of self-similarity, one of the main characteristics of a fractal. Despite the many conceptual advantages of the FrMS, it has not been successfully elaborated and implemented to date because of the difficulties involved in doing so. In this paper, the static functions and dynamic activities of each agent are modeled using the unified modeling language (UML). Then, relationships among agents, working mechanisms of each agent, and several fractal-specific characteristics (self-similarity, self-organization, and goal-orientation) are modeled using the UML. Then, a method for dealing with several types of information such as products, orders, and resources in the FrMS is presented. Finally, a preliminary prototype for the FrMS using Aglets™ is presented. © 2003 Elsevier B.V. All rights reserved.
• Son, Y. J., Jones, A. T., & Wysk, R. A. (2003). Component based simulation modeling from neutral component libraries. Computers and Industrial Engineering, 45(1), 141-165.
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  Abstract: Researchers at the National Institute of Standards and Technology have proposed the development of libraries of formal, neutral models of simulation components. The availability of such libraries would simplify the generation of simulation models, enable reuse of existing models construction of complicated models from simpler ones, and speed Internet-based simulation services. The result would be a dramatic increase in the use of simulation for decision-making and control in manufacturing. In this paper, we describe a collection of formal, neutral models for a discrete-event simulation of the flow of jobs through a job shop, where the simulation executes jobs based on a pre-provided schedule. We then derive a database structure from these formal models and discuss the population of that database with the data entries for a sample job shop. We then examine the translators we developed to go from the neutral representation of the simulation components to the representation required by Arena. Finally, we compare this routing aspect of translator to the routing aspects of a translator we built for ProModel. © 2003 Elsevier Science Ltd. All rights reserved.
• Son, Y. J., Wysk, R. A., & Jones, A. T. (2003). Simulation-based shop floor control: Formal model, model generation and control interface. IIE Transactions (Institute of Industrial Engineers), 35(1), 29-48.
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  Abstract: In this paper, a structure and architecture for the rapid realization of a simulation-based real-time shop floor control system for a discrete part manufacturing system is presented. The research focuses on automatic simulation model and execution system generation from a production resource model. An Automatic Execution Model Generator (AEMG) has been designed and implemented for generating a Message-based Part State Graph (MPSG)-based shop level execution model. An Automatic Simulation Model Generator (ASMG) has been designed and implemented for generating an Arena simulation model based on a resource model (MS Access 97) and an MPSG-based shop level execution model. A commercial finite capacity scheduler, Tempo, has been used to provide schedule information for the Arena simulation model. This research has been implemented and tested for six manufacturing systems, including The Pennsylvania State University CIM laboratory.
• Son, Y., Joshi, S. B., Wysk, R. A., & Smith, J. S. (2002). Simulation-based shop floor control. Journal of Manufacturing Systems, 21(5), 380-394.
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  Abstract: This paper presents an overview of simulation-based shop floor control. Much of the work described is based on research conducted in the Computer Integrated Manufacturing (CIM) Lab at The Pennsylvania State University, the Texas A&M Computer Aided Manufacturing Lab (TAMCAM), Technion in Israel, and the University of Arizona CIM lab over the past decade. In this approach, a discrete event simulation is used not only as a traditional analysis and evaluation tool but also as a task generator that drives shop floor operations in real time. To enable this, a special feature of the Arena™ simulation language was used whereby the simulation model interacts directly with a shop floor execution system by sending and receiving messages. This control simulation reads process plans and master production orders from external data-bases that are updated by a process planning system and coordinated via an external business system. The control simulation also interacts with other external programs such as a planner, a scheduler, and an error detection and recovery function. In this paper, the architecture, implementation, and the integration of all the components of the proposed simulation-based control system are described in detail. Finally, extensions to this approach, including automatic model generation, are described.
• Venkateswaran, J., Son, Y., & Kulvatunyou, B. (2002). Investigation of influence of modeling fidelities on supply chain dynamics. Winter Simulation Conference Proceedings, 2, 1183-1191.
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  Abstract: In this paper, a three-echelon supply chain model is analyzed to determine strategies to reduce the supply chain system dynamics. Uniqueness of this research stems from the use of multiple models with varying degrees of detail representing the same supply chain. The significance of a detailed supply chain model on the quality of result is made clear. Factors employed to build an abstract to a detailed model include: transportation and production delay, demand at the retailer, and production and transportation capacity. It is shown that the system dynamics itself varies with increasing detail in the model. In addition, it is examined to see if a strategy found effective in improving the system dynamics with an abstract model is effective with a detailed model. It is established that the strategy found to be the most effective on an abstract model is not always the best strategy for the real supply chain.
• Son, Y. J., & Wysk, R. A. (2001). Automatic simulation model generation for simulation-based, real-time shop floor control. Computers in Industry, 45(3), 291-308.
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  Abstract: This paper presents a structure and architecture for automatic simulation model generation (for very detailed simulation models intended to be used for real-time simulation-based shop floor control). The simulation model code is generated from a shop floor resource model and a shop floor control model. The shop floor resource model provides much of the static information for the simulation model; while a shop level control model provides much of the dynamic information required by the simulation model. The simulation code generated can be used for traditional system analysis, but more importantly, it can also be used to control the manufacturing system by sending and receiving messages using an Ethernet communication link to a high-level task executing system. Six manufacturing systems are used to illustrate and test the validity of the simulation model generation methodology. Finally, factory level planning and scheduling activities using the generated simulation model are described. © 2001 Elsevier Science B.V.
• Son, Y., Venkateswaran, J., Yaseen, K., & Mopidevi, R. (2001). Initial research on schedule interface with shop floor control system. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 2, 1282-1287.
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  Abstract: This paper investigates integration of scheduling with a shop floor control system in general, and simulation-based shop floor control system in particular. Simplifications and assumptions made in traditional operations scheduling, such as disregarding material handling and buffers, have created questions concerning the fidelity of scheduling and implementing them in production systems. Since the simulation is used as an online task generator in a simulation-based control system, invalid schedules cause catastrophic results or system deadlocking (blocking) in the shop floor. In this paper, the assumptions made in scheduling are investigated in order to determine if schedules can be actually implemented as intended. In addition, two prominent scheduling algorithms, Johnson's Algorithm and Jackson's Algorithm, are investigated to determine whether and in what conditions they work properly.
• Steele, J., Son, Y., & Wysk, R. A. (2001). Resource modeling for the integration of the manufacturing enterprise. Journal of Manufacturing Systems, 19(6), 407-425.
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  Abstract: Researchers are beginning to develop taxonomies of different knowledge domains in order to specify the requirements of engineering functions in various manufacturing enterprises. These interrelated functions include product design, process planning, capacity planning, production costing, quality control, acquisition or reconfiguration of resources, planning and scheduling of shop activities, and execution of shop activities. These taxonomies and functions are not typically integrated in today's manufacturing enterprise. This results in inefficient manual transfer of knowledge between domains and the unavailability of critical information required for decision making. Object-oriented design methodologies are useful for modeling diverse information and behavior. Furthermore, planning, analysis, and control of resources such as machine tools, fixtures, and tooling increasingly dominate the engineering functions. This paper demonstrates how to integrate these functions with an object-oriented resource model that links information from different knowledge domains. These functions are implemented using different software packages that can easily access the common resource data because the data are embedded in the resource class structure. This resource model is based on software objects that have a one-to-one correspondence with physical objects. This resource model is illustrated using object-oriented software, but the model may also be applied to distributed object and agent architectures.
• Venkateswaran, J., Yaseen, M., & Son, Y. (2001). Distributed simulation: An enabling technology for the evaluation of virtual enterprises. Winter Simulation Conference Proceedings, 2, 856-862.
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  Abstract: This paper presents an application distributed simulation to the evaluation of virtual enterprises. Each company or candidate can use a simulation of its facilities to determine if it has the capability to perform its individual function in the virtual enterprise. Then, these simulations can be integrated into a distributed simulation of the complete enterprise, and used to predict the viability and profitability of the proposed product collaboration. In this paper, a prototype distributed simulation for such a purpose is presented. First, information flows as well as material flows among members in a virtual enterprise are identified using IDEFØ, a formal function modeling method. Sequences of the identified functions are then presented using the finite state automata formalism. These interactions are then implemented for a commercial simulation package. Finally, a distributed simulation composed of three individual simulations is successfully tested across platforms over both the internet and the local area network.
• Son, Y. J., Jones, A. T., & Wysk, R. A. (2000). Automatic generation of simulation models from neutral libraries: An example. Winter Simulation Conference Proceedings, 2, 1558-1567.
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  Abstract: Researchers at the National Institute of Standards and Technology have proposed the development of neutral libraries of simulation components. The availability of such libraries would simplify the generation of simulation models, enable component-based modeling, and speed Internet-based simulation services. The result would be a reduction in the complexity of simulation modeling and analysis. In this paper, we consider a discrete-event simulation of the flow of jobs through a job shop. We describe the information requirements for the components in that simulation and provide formal models based on those requirements. We then derive a database structure from these formal models and discuss the population of that database with the data entries for a sample job shop. Finally, we examine the translators we developed to go from the neutral representation of the simulation components to the representation required by a commercial simulation package.
• Son, Y., & Wysk, R. A. (2000). A formal structure and implementation of a robotic material handling controller in an automated shop floor environment. International Journal of Production Research, 38(15), 3553-3572.
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  Abstract: This paper proposes a formal structure and framework for a robotic material handling (MH) equipment-level controller in a hierarchical shop floor control architecture. This framework essentially attempts to integrate shop-level process planning with material handling at the workplace. Handling operations are therefore integrated with manufacturing functions in order to ensure 'Seamless' material transfer and processing. The responsibilities of the MH equipment controller include: interface with a MH robot; read and interpret handling plans from a database (in the form of an AND/OR graph); plan and schedule MH activities; perform path planning and grasp planning for the required task; generate generic robot-level commands automatically; and convert generic robot-level commands to robot-specific instructions. A MH equipment-level controller has been designed and implemented for a PUMA 560 robot in the CIM lab at the Pennsylvania State University. The proposed controller can work for various situations and job volumes. In addition, by creating the framework described in this paper, extending the concept for other parts and obstacles with various features, coordinating the vision system or the CAD system to the proposed controller, and combining complete path planning and grasp planning systems, a fully operational MH equipment-level controller can be realized.

Proceedings Publications

• Jain, S., Lee, S., Barber, S., Chang, E., & Son, Y. (2019, APRIL 29 - May 2). DDDAS-based Adaptive Surgical Simulation using Mixed Reality. In 2019 Summer Simulation Conference, Tucson, AZ.
• Masoud, S., Chowdhury, B., Son, Y., & Tronstad, R. (2019, May, 2019). Markov-chain Monte-Carlo Sampling for Optimal Fidelity Determination in Dynamic Decision-Making. In 2019 IISE Annual Meeting.
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  Received the best track paper award (1st place)
• Masoud, S., Chowdhury, B., Son, Y., Kubota, C., & Tronstad, R. (2019, 2019 International Symposium on Vegetable Grafting). GRANDES: An Online Decision Support Tool for Grafting Nurseries. In 2019 International Symposium on Vegetable Grafting.
• Meng, C., Kim, S., Son, Y. -., & Kubota, C. -. (2013, December). A system-based simulation model aggregation framework for seedling propagation system. In 2013 Winter Simulation Conference.

Presentations

• Nageshwaraniyer, S. S., Kim, K., & Son, Y. (2014, DECEMBER). Optimal Blast Design Using a Discrete-Event Simulation Model in a Hard Rock Mine. SME Arizona.

Poster Presentations

• Lee, S., Minaeian, S., Yuan, Y., Son, Y., & Liu, J. (2017, Spetember). DDDAMS-based Border Surveillance and Crowd Control via Aerostats, UAVs, and Ground Sensors. InfoSymbiotic:DDDAS17. University of Arizona.
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  FAC 2017 conference presentation/paper submission.