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A Hybrid Metaheuristic for the Unrelated Parallel Machine Scheduling Problem

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  • Dung-Ying Lin

    (Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu 30013, Taiwan)

  • Tzu-Yun Huang

    (Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu 30013, Taiwan)

Abstract

The unrelated parallel machine scheduling problem aims to assign jobs to independent machines with sequence-dependent setup times so that the makespan is minimized. When many practical considerations are introduced, solving the resulting problem is challenging, especially when problems of realistic sizes are of interest. In this study, in addition to the conventional objective of minimizing the makespan, we further consider the burn-in (B/I) procedure that is required in practice; we need to ensure that the scheduling results satisfy the B/I ratio constrained by the equipment. To solve the resulting complicated problem, we propose a population-based simulated annealing algorithm embedded with a variable neighborhood descent technique. Empirical results show that the proposed solution strategy outperforms a commonly used commercial optimization package; it can obtain schedules that are better than the schedules used in practice, and it does so in a more efficient manner.

Suggested Citation

  • Dung-Ying Lin & Tzu-Yun Huang, 2021. "A Hybrid Metaheuristic for the Unrelated Parallel Machine Scheduling Problem," Mathematics, MDPI, vol. 9(7), pages 1-20, April.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:7:p:768-:d:528578
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    References listed on IDEAS

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    Cited by:

    1. Chun-Lung Chen, 2023. "An Iterated Population-Based Metaheuristic for Order Acceptance and Scheduling in Unrelated Parallel Machines with Several Practical Constraints," Mathematics, MDPI, vol. 11(6), pages 1-14, March.

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