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An effective metaheuristic algorithm for flowshop scheduling with deteriorating jobs

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  • Hongfeng Wang

    (Northeastern University)

  • Min Huang

    (Northeastern University)

  • Junwei Wang

    (The University of Hong Kong)

Abstract

The deterioration effect in flowshop scheduling has gained a growing concern from the community of operational research in recent years. However, all of existing studies focus on two- or three-machine flow shops. In this paper, a m-machine $$(m>3)$$ ( m > 3 ) flowshop scheduling problem (FSSP) with deteriorating jobs is investigated and a novel metaheuristic algorithm called multi-verse optimizer (MVO) is employed to solve it. The MVO algorithm can accomplish the optimization process via exchanging objects of universes through white/black hole and wormhole tunnels. In the novel MVO algorithm, a new elitist selection scheme is designed to construct the effective white/black hole tunnels, whereas two different local search operators are hybridized and embedded to further enhance the exploitation capability. Experimental results indicate that the proposed algorithm can achieve the satisfactory performance in solving the investigated FSSP with deteriorating jobs.

Suggested Citation

  • Hongfeng Wang & Min Huang & Junwei Wang, 2019. "An effective metaheuristic algorithm for flowshop scheduling with deteriorating jobs," Journal of Intelligent Manufacturing, Springer, vol. 30(7), pages 2733-2742, October.
    • Handle: RePEc:spr:joinma:v:30:y:2019:i:7:d:10.1007_s10845-018-1425-8
    DOI: 10.1007/s10845-018-1425-8
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    References listed on IDEAS

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