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A Global Neighborhood with Hill-Climbing Algorithm for Fuzzy Flexible Job Shop Scheduling Problem

Author

Listed:
  • Juan Carlos Seck-Tuoh-Mora

    (Área Académica de Ingeniería, Instituto de Ciencias Básicas e Ingeniería, Universidad Autónoma del Estado de Hidalgo, Carr. Pachuca-Tulancingo km. 4.5, Pachuca 42184, Hidalgo, Mexico
    These authors contributed equally to this work.)

  • Nayeli Jazmín Escamilla-Serna

    (Área Académica de Ingeniería, Instituto de Ciencias Básicas e Ingeniería, Universidad Autónoma del Estado de Hidalgo, Carr. Pachuca-Tulancingo km. 4.5, Pachuca 42184, Hidalgo, Mexico
    These authors contributed equally to this work.)

  • Leonardo Javier Montiel-Arrieta

    (Área Académica de Ingeniería, Instituto de Ciencias Básicas e Ingeniería, Universidad Autónoma del Estado de Hidalgo, Carr. Pachuca-Tulancingo km. 4.5, Pachuca 42184, Hidalgo, Mexico)

  • Irving Barragan-Vite

    (Área Académica de Ingeniería, Instituto de Ciencias Básicas e Ingeniería, Universidad Autónoma del Estado de Hidalgo, Carr. Pachuca-Tulancingo km. 4.5, Pachuca 42184, Hidalgo, Mexico)

  • Joselito Medina-Marin

    (Área Académica de Ingeniería, Instituto de Ciencias Básicas e Ingeniería, Universidad Autónoma del Estado de Hidalgo, Carr. Pachuca-Tulancingo km. 4.5, Pachuca 42184, Hidalgo, Mexico)

Abstract

The Flexible Job Shop Scheduling Problem (FJSSP) continues to be studied extensively to test new metaheuristics and because of its closeness to current production systems. A variant of the FJSSP uses fuzzy processing times instead of fixed times. This paper proposes a new algorithm for FJSSP with fuzzy processing times called the global neighborhood with hill-climbing algorithm (GN-HC). This algorithm performs solution exploration using simple operators concurrently for global search neighborhood handling. For local search, random restart hill-climbing is applied at each solution to find the best machine for each operation. For the selection of operations in hill climbing, a record of the operations defining the fuzzy makespan is employed to use them as a critical path. Finally, an estimation of the crisp makespan with the longest processing times in hill climbing is made to improve the speed of the GN-HC. The GN-HC is compared with other recently proposed methods recognized for their excellent performance, using 6 FJSSP instances with fuzzy times. The obtained results show satisfactory competitiveness for GN-HC compared to state-of-the-art algorithms. The GN-HC implementation was performed in Matlab and can be found on GitHub (check Data Availability Statement at the end of the paper).

Suggested Citation

  • Juan Carlos Seck-Tuoh-Mora & Nayeli Jazmín Escamilla-Serna & Leonardo Javier Montiel-Arrieta & Irving Barragan-Vite & Joselito Medina-Marin, 2022. "A Global Neighborhood with Hill-Climbing Algorithm for Fuzzy Flexible Job Shop Scheduling Problem," Mathematics, MDPI, vol. 10(22), pages 1-13, November.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:22:p:4233-:d:971104
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    References listed on IDEAS

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    1. J. Behnamian, 2016. "Survey on fuzzy shop scheduling," Fuzzy Optimization and Decision Making, Springer, vol. 15(3), pages 331-366, September.
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