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Simulation optimization in the era of Industrial 4.0 and the Industrial Internet

Author

Listed:
  • Jie Xu
  • Edward Huang
  • Liam Hsieh
  • Loo Hay Lee
  • Qing-Shan Jia
  • Chun-Hung Chen

Abstract

Simulation is an established tool for predicting and evaluating the performance of complex stochastic systems that are analytically intractable. Recent research in simulation optimization and explosive growth in computing power have made it feasible to use simulations to optimize the design and operations of systems directly. Concurrently, ubiquitous sensing, pervasive computing, and unprecedented systems interconnectivity have ushered in a new era of industrialization (the so-called Industrial 4.0/Industrial Internet). In this article, we argue that simulation optimization is a decision-making tool that can be applied to many scenarios to tremendous effect. By capitalizing on an unprecedented integration of sensing, computing, and control, simulation optimization provides the “smart brain” required to drastically improve the efficiency of industrial systems. We explore the potential of simulation optimization and discuss how simulation optimization can be applied, with an emphasis on the recent development of multi-fidelity/multi-scale simulation optimization.

Suggested Citation

  • Jie Xu & Edward Huang & Liam Hsieh & Loo Hay Lee & Qing-Shan Jia & Chun-Hung Chen, 2016. "Simulation optimization in the era of Industrial 4.0 and the Industrial Internet," Journal of Simulation, Taylor & Francis Journals, vol. 10(4), pages 310-320, November.
    • Handle: RePEc:taf:tjsmxx:v:10:y:2016:i:4:p:310-320
    DOI: 10.1057/s41273-016-0037-6
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    Cited by:

    1. Badakhshan, Ehsan & Ball, Peter, 2023. "A simulation-optimization approach for integrating physical and financial flows in a supply chain under economic uncertainty," Operations Research Perspectives, Elsevier, vol. 10(C).
    2. Jingxu Xu & Zeyu Zheng, 2023. "Gradient-Based Simulation Optimization Algorithms via Multi-Resolution System Approximations," INFORMS Journal on Computing, INFORMS, vol. 35(3), pages 633-651, May.

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