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Embedding ant system in genetic algorithm for re-entrant hybrid flow shop scheduling problems with time window constraints

Author

Listed:
  • Chettha Chamnanlor

    (Khon Kaen University)

  • Kanchana Sethanan

    (Khon Kaen University)

  • Mitsuo Gen

    (Tokyo University of Science
    Fuzzy Logic Systems Institute)

  • Chen-Fu Chien

    (National Tsing Hua University)

Abstract

This paper focuses on minimizing the makespan for a reentrant hybrid flow shop scheduling problem with time window constraints (RHFSTW), which is often found in manufacturing systems producing the slider part of hard-disk drive products, in which production needs to be monitored to ensure high quality. For this reason, production time control is required from the starting-time-window stage to the ending-time-window stage. Because of the complexity of the RHFSTW problem, in this paper, genetic algorithm hybridized ant colony optimization (GACO) is proposed to be used as a support tool for scheduling. The results show that the GACO can solve problems optimally with reasonable computational effort.

Suggested Citation

  • Chettha Chamnanlor & Kanchana Sethanan & Mitsuo Gen & Chen-Fu Chien, 2017. "Embedding ant system in genetic algorithm for re-entrant hybrid flow shop scheduling problems with time window constraints," Journal of Intelligent Manufacturing, Springer, vol. 28(8), pages 1915-1931, December.
    • Handle: RePEc:spr:joinma:v:28:y:2017:i:8:d:10.1007_s10845-015-1078-9
    DOI: 10.1007/s10845-015-1078-9
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    References listed on IDEAS

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    1. Dugardin, Frédéric & Yalaoui, Farouk & Amodeo, Lionel, 2010. "New multi-objective method to solve reentrant hybrid flow shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 203(1), pages 22-31, May.
    2. 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.
    3. Ruiz, Ruben & Maroto, Concepcion & Alcaraz, Javier, 2005. "Solving the flowshop scheduling problem with sequence dependent setup times using advanced metaheuristics," European Journal of Operational Research, Elsevier, vol. 165(1), pages 34-54, August.
    4. Haipeng Zhang & Mitsuo Gen, 2009. "A parallel hybrid ant colony optimisation approach for job-shop scheduling problem," International Journal of Manufacturing Technology and Management, Inderscience Enterprises Ltd, vol. 16(1/2), pages 22-41.
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    Cited by:

    1. Konstantinos S. Boulas & Georgios D. Dounias & Chrissoleon T. Papadopoulos, 2023. "A hybrid evolutionary algorithm approach for estimating the throughput of short reliable approximately balanced production lines," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 823-852, February.
    2. Zheng Xiao & Zhenan Wang & Deng Liu & Hui Wang, 2022. "A path planning algorithm for PCB surface quality automatic inspection," Journal of Intelligent Manufacturing, Springer, vol. 33(6), pages 1829-1841, August.
    3. Mohamed Kriouich & Hicham Sarir, 2024. "Artificial Intelligence Application in Production Scheduling Problem Systematic Literature Review: Bibliometric Analysis, Research Trend, and Knowledge Taxonomy," SN Operations Research Forum, Springer, vol. 5(2), pages 1-24, June.
    4. Maedeh Fasihi & Reza Tavakkoli-Moghaddam & Fariborz Jolai, 2023. "A bi-objective re-entrant permutation flow shop scheduling problem: minimizing the makespan and maximum tardiness," Operational Research, Springer, vol. 23(2), pages 1-41, June.
    5. Fan Yang & Roel Leus, 2021. "Scheduling hybrid flow shops with time windows," Journal of Heuristics, Springer, vol. 27(1), pages 133-158, April.

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