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Matheuristic algorithms for minimizing total tardiness in the m-machine flow-shop scheduling problem

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  • Quang Chieu Ta

    (Université François Rabelais de Tours)

  • Jean-Charles Billaut

    (Université François Rabelais de Tours)

  • Jean-Louis Bouquard

    (Université François Rabelais de Tours)

Abstract

We consider in this paper the m-machine permutation flow-shop problem with total tardiness minimization. We propose several matheuristic algorithms, which are an hybridization of a local search and an exact resolution method. The matheuristics are compared to a genetic algorithm. Computational experiments are performed on benchmark instances and the results show the good performances of the matheuristic algorithms. Finally, some future research directions are given.

Suggested Citation

  • Quang Chieu Ta & Jean-Charles Billaut & Jean-Louis Bouquard, 2018. "Matheuristic algorithms for minimizing total tardiness in the m-machine flow-shop scheduling problem," Journal of Intelligent Manufacturing, Springer, vol. 29(3), pages 617-628, March.
    • Handle: RePEc:spr:joinma:v:29:y:2018:i:3:d:10.1007_s10845-015-1046-4
    DOI: 10.1007/s10845-015-1046-4
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    References listed on IDEAS

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    1. Osman, IH & Potts, CN, 1989. "Simulated annealing for permutation flow-shop scheduling," Omega, Elsevier, vol. 17(6), pages 551-557.
    2. Portmann, M. -C. & Vignier, A. & Dardilhac, D. & Dezalay, D., 1998. "Branch and bound crossed with GA to solve hybrid flowshops," European Journal of Operational Research, Elsevier, vol. 107(2), pages 389-400, June.
    3. Vallada, Eva & Ruiz, Rubén, 2010. "Genetic algorithms with path relinking for the minimum tardiness permutation flowshop problem," Omega, Elsevier, vol. 38(1-2), pages 57-67, February.
    4. Nawaz, Muhammad & Enscore Jr, E Emory & Ham, Inyong, 1983. "A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem," Omega, Elsevier, vol. 11(1), pages 91-95.
    5. Jianzhong Du & Joseph Y.-T. Leung, 1990. "Minimizing Total Tardiness on One Machine is NP-Hard," Mathematics of Operations Research, INFORMS, vol. 15(3), pages 483-495, August.
    6. Tasgetiren, M. Fatih & Liang, Yun-Chia & Sevkli, Mehmet & Gencyilmaz, Gunes, 2007. "A particle swarm optimization algorithm for makespan and total flowtime minimization in the permutation flowshop sequencing problem," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1930-1947, March.
    7. Nowicki, Eugeniusz & Smutnicki, Czeslaw, 1996. "A fast tabu search algorithm for the permutation flow-shop problem," European Journal of Operational Research, Elsevier, vol. 91(1), pages 160-175, May.
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    Cited by:

    1. 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.
    2. Said Aqil & Karam Allali, 2021. "On a bi-criteria flow shop scheduling problem under constraints of blocking and sequence dependent setup time," Annals of Operations Research, Springer, vol. 296(1), pages 615-637, January.
    3. Mohammad Mahdi Ahmadian & Amir Salehipour, 2021. "The just-in-time job-shop scheduling problem with distinct due-dates for operations," Journal of Heuristics, Springer, vol. 27(1), pages 175-204, April.
    4. Gang Xuan & Win-Chin Lin & Shuenn-Ren Cheng & Wei-Lun Shen & Po-An Pan & Chih-Ling Kuo & Chin-Chia Wu, 2022. "A Robust Single-Machine Scheduling Problem with Two Job Parameter Scenarios," Mathematics, MDPI, vol. 10(13), pages 1-17, June.

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