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Simulation Optimization: A Review and Exploration in the New Era of Cloud Computing and Big Data

Author

Listed:
  • Jie Xu

    (Department of Systems Engineering and Operations Research, 4400 University Dr., MS 4A6, George Mason University, Fairfax VA 22030, USA)

  • Edward Huang

    (Department of Systems Engineering and Operations Research, 4400 University Dr., MS 4A6, George Mason University, Fairfax VA 22030, USA)

  • Chun-Hung Chen

    (Department of Systems Engineering and Operations Research, 4400 University Dr., MS 4A6, George Mason University, Fairfax VA 22030, USA)

  • Loo Hay Lee

    (Department of Industrial and Systems Engineering, National University of Singapore, Singapore 119077, Singapore)

Abstract

Recent advances in simulation optimization research and explosive growth in computing power have made it possible to optimize complex stochastic systems that are otherwise intractable. In the first part of this paper, we classify simulation optimization techniques into four categories based on how the search is conducted. We provide tutorial expositions on representative methods from each category, with a focus in recent developments, and compare the strengths and limitations of each category. In the second part of this paper, we review applications of simulation optimization in various contexts, with detailed discussions on health care, logistics, and manufacturing systems. Finally, we explore the potential of simulation optimization in the new era. Specifically, we discuss how simulation optimization can benefit from cloud computing and high-performance computing, its integration with big data analytics, and the value of simulation optimization to help address challenges in engineering design of complex systems.

Suggested Citation

  • Jie Xu & Edward Huang & Chun-Hung Chen & Loo Hay Lee, 2015. "Simulation Optimization: A Review and Exploration in the New Era of Cloud Computing and Big Data," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 32(03), pages 1-34.
  • Handle: RePEc:wsi:apjorx:v:32:y:2015:i:03:n:s0217595915500190
    DOI: 10.1142/S0217595915500190
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    3. Roberto Aringhieri & Patrick Hirsch & Marion S. Rauner & Melanie Reuter-Oppermanns & Margit Sommersguter-Reichmann, 2022. "Central European journal of operations research (CJOR) “operations research applied to health services (ORAHS) in Europe: general trends and ORAHS 2020 conference in Vienna, Austria”," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(1), pages 1-18, March.
    4. James T. Lin & Chun-Chih Chiu & Edward Huang & Hung-Ming Chen, 2018. "A Multi-Fidelity Model Approach for Simultaneous Scheduling of Machines and Vehicles in Flexible Manufacturing Systems," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(01), pages 1-20, February.
    5. Jia, Shuai & Li, Chung-Lun & Xu, Zhou, 2020. "A simulation optimization method for deep-sea vessel berth planning and feeder arrival scheduling at a container port," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 174-196.
    6. Wai Kin Victor Chan, 2016. "Linear Programming Formulation of Idle Times for Single-Server Discrete-Event Simulation Models," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(05), pages 1-17, October.
    7. Shuang Xiao & Guo Li & Yunjing Jia, 2017. "Estimating the Constant Elasticity of Variance Model with Data-Driven Markov Chain Monte Carlo Methods," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(01), pages 1-23, February.
    8. Li, Na & Zhang, Yue & Teng, De & Kong, Nan, 2021. "Pareto optimization for control agreement in patient referral coordination," Omega, Elsevier, vol. 101(C).
    9. Yong Tian & Bojia Ye & Marc Sáez Estupiñá & Lili Wan, 2018. "Stochastic Simulation Optimization for Route Selection Strategy Based on Flight Delay Cost," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(06), pages 1-24, December.
    10. P. Troy & N. Lahrichi & D. Porubska & L. Rosenberg, 2020. "Fine-grained simulation optimization for the design and operations of a multi-activity clinic," Flexible Services and Manufacturing Journal, Springer, vol. 32(3), pages 599-628, September.
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    12. Giulia Pedrielli & K. Selcuk Candan & Xilun Chen & Logan Mathesen & Alireza Inanalouganji & Jie Xu & Chun-Hung Chen & Loo Hay Lee, 2019. "Generalized Ordinal Learning Framework (GOLF) for Decision Making with Future Simulated Data," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(06), pages 1-35, December.
    13. Hainan Guo & Haobin Gu & Yu Zhou & Jiaxuan Peng, 2022. "A data-driven multi-fidelity simulation optimization for medical staff configuration at an emergency department in Hong Kong," Flexible Services and Manufacturing Journal, Springer, vol. 34(2), pages 238-262, June.
    14. Yu Zhao & Xi Zhang & Zhongshun Shi & Lei He, 2017. "Grain Price Forecasting Using a Hybrid Stochastic Method," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(05), pages 1-24, October.
    15. Wentao Wu & Wai Kin Victor Chan & Lei Chi & Zhiguo Gong, 2017. "Identifying a Set of Key Members in Social Networks Using SDP-Based Stochastic Search and Integer Programming Algorithms," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(03), pages 1-22, June.
    16. Wang, Tianxiang & Xu, Jie & Hu, Jian-Qiang & Chen, Chun-Hung, 2023. "Efficient estimation of a risk measure requiring two-stage simulation optimization," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1355-1365.
    17. Pedrielli, Giulia & Wang, Songhao & Ng, Szu Hui, 2020. "An extended Two-Stage Sequential Optimization approach: Properties and performance," European Journal of Operational Research, Elsevier, vol. 287(3), pages 929-945.
    18. Miranda, Rafael de Carvalho & Montevechi, José Arnaldo Barra & da Silva, Aneirson Francisco & Marins, Fernando Augusto Silva, 2017. "Increasing the efficiency in integer simulation optimization: Reducing the search space through data envelopment analysis and orthogonal arrays," European Journal of Operational Research, Elsevier, vol. 262(2), pages 673-681.
    19. Siyang Gao & Weiwei Chen & Leyuan Shi, 2017. "A New Budget Allocation Framework for the Expected Opportunity Cost," Operations Research, INFORMS, vol. 65(3), pages 787-803, June.
    20. Qi Zhang & Jiaqiao Hu, 2019. "Simulation Optimization Using Multi-Time-Scale Adaptive Random Search," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(06), pages 1-34, December.
    21. Robert Cuckler & Kuo-Hao Chang & Liam Y. Hsieh, 2017. "Optimal Parallel Machine Allocation Problem in IC Packaging Using IC-PSO: An Empirical Study," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(06), pages 1-20, December.
    22. Jianpei Wen & Hanyu Jiang & Jie Song, 2019. "A Stochastic Queueing Model for Capacity Allocation in the Hierarchical Healthcare Delivery System," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(01), pages 1-24, February.
    23. Pai Liu & Xi Zhang & Zhongshun Shi & Zewen Huang, 2017. "Simulation Optimization for MRO Systems Operations," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(02), pages 1-23, April.

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