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A local search method for permutation flow shop scheduling

Author

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  • W Q Huang

    (Huazhong University of Science and Technology)

  • L Wang

    (Huazhong University of Science and Technology)

Abstract

It is well known that a local search method, a widely used approach for solving the permutation flow shop scheduling problem, can easily be trapped at a local optimum. In this paper, we propose two escape-from-trap procedures to move away from local optima. Computational experiments carried out on a standard set of instances show that this heuristic algorithm generally outperforms an effective approximation algorithm.

Suggested Citation

  • W Q Huang & L Wang, 2006. "A local search method for permutation flow shop scheduling," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(10), pages 1248-1251, October.
  • Handle: RePEc:pal:jorsoc:v:57:y:2006:i:10:d:10.1057_palgrave.jors.2602106
    DOI: 10.1057/palgrave.jors.2602106
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    References listed on IDEAS

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    5. Chen, Chuen-Lung & Vempati, Venkateswara S. & Aljaber, Nasser, 1995. "An application of genetic algorithms for flow shop problems," European Journal of Operational Research, Elsevier, vol. 80(2), pages 389-396, January.
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    11. JC-H Pan & J-S Chen, 2003. "Minimizing makespan in re-entrant permutation flow-shops," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(6), pages 642-653, June.
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    Cited by:

    1. Zhaoyang Yang & Guojun Zhang & Haiping Zhu, 2016. "Multi-neighborhood based path relinking for two-sided assembly line balancing problem," Journal of Combinatorial Optimization, Springer, vol. 32(2), pages 396-415, August.
    2. Fernandez-Viagas, Victor & Ruiz, Rubén & Framinan, Jose M., 2017. "A new vision of approximate methods for the permutation flowshop to minimise makespan: State-of-the-art and computational evaluation," European Journal of Operational Research, Elsevier, vol. 257(3), pages 707-721.

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