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A Newton-based heuristic algorithm for multi-objective flexible job-shop scheduling problem

Author

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  • Miguel A. Fernández Pérez

    (Pontifícia Universidade Católica do Rio de Janeiro)

  • Fernanda M. P. Raupp

    (Pontifícia Universidade Católica do Rio de Janeiro)

Abstract

We propose a new hierarchical heuristic algorithm for multi-objective flexible job-shop scheduling problems. The proposed method is an adaptation of the Newton’s method for continuous multi-objective unconstrained optimization problems, belonging to the class of multi-criteria descent methods. Numerical experiments with the proposed method are presented. The potential of the proposed method is demonstrated by comparing the obtained results with the known results of existing methods that solve the same test instances.

Suggested Citation

  • Miguel A. Fernández Pérez & Fernanda M. P. Raupp, 2016. "A Newton-based heuristic algorithm for multi-objective flexible job-shop scheduling problem," Journal of Intelligent Manufacturing, Springer, vol. 27(2), pages 409-416, April.
    • Handle: RePEc:spr:joinma:v:27:y:2016:i:2:d:10.1007_s10845-014-0872-0
    DOI: 10.1007/s10845-014-0872-0
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    References listed on IDEAS

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    1. Kacem, Imed & Hammadi, Slim & Borne, Pierre, 2002. "Pareto-optimality approach for flexible job-shop scheduling problems: hybridization of evolutionary algorithms and fuzzy logic," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 60(3), pages 245-276.
    2. Stéphane Dauzère-Pérès & Jan Paulli, 1997. "An integrated approach for modeling and solving the general multiprocessor job-shop scheduling problem using tabu search," Annals of Operations Research, Springer, vol. 70(0), pages 281-306, April.
    3. Konak, Abdullah & Coit, David W. & Smith, Alice E., 2006. "Multi-objective optimization using genetic algorithms: A tutorial," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 992-1007.
    4. Moslehi, Ghasem & Mahnam, Mehdi, 2011. "A Pareto approach to multi-objective flexible job-shop scheduling problem using particle swarm optimization and local search," International Journal of Production Economics, Elsevier, vol. 129(1), pages 14-22, January.
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    Cited by:

    1. Alper Türkyılmaz & Özlem Şenvar & İrem Ünal & Serol Bulkan, 2020. "A research survey: heuristic approaches for solving multi objective flexible job shop problems," Journal of Intelligent Manufacturing, Springer, vol. 31(8), pages 1949-1983, December.

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