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A Multi-Fidelity Model Approach for Simultaneous Scheduling of Machines and Vehicles in Flexible Manufacturing Systems

Author

Listed:
  • James T. Lin

    (Department of Industrial Engineering and Engineering Management, National Tsing Hua University, No. 101, Section 2, Guangfu Road, Hsinchu 300, Taiwan R. O. C.)

  • Chun-Chih Chiu

    (Department of Industrial Engineering and Engineering Management, National Tsing Hua University, No. 101, Section 2, Guangfu Road, Hsinchu 300, Taiwan R. O. C.)

  • Edward Huang

    (Department of System Engineering and Operations Research, George Mason University, Fairfax, VA 22030, USA)

  • Hung-Ming Chen

    (Department of Industrial Engineering and Engineering Management, National Tsing Hua University, No. 101, Section 2, Guangfu Road, Hsinchu 300, Taiwan R. O. C.)

Abstract

Driven by sensor technologies and Internet of Things, massive real-time data from highly interconnected devices are available, which enables the improvement of decision-making quality. Scheduling of such production systems can be challenging as it must incorporate the latest data and be able to re-plan quickly. In this research, a multi-fidelity model for simultaneous scheduling problem of machines and vehicles at flexible manufacturing system has been proposed. In order to improve the computational efficiency, we extend the framework, called multi-fidelity optimization with ordinal transformation and optimal sampling, with combining with the K-means method. The proposed framework enables the benefits of both fast and inexpensive low-fidelity models with accurate but more expensive high-fidelity models. Results show that this approach can significantly decrease computational cost compared with other algorithms in the literature.

Suggested Citation

  • 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.
    • Handle: RePEc:wsi:apjorx:v:35:y:2018:i:01:n:s0217595918500057
    DOI: 10.1142/S0217595918500057
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    References listed on IDEAS

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    3. 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.
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