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A research survey: heuristic approaches for solving multi objective flexible job shop problems

Author

Listed:
  • Alper Türkyılmaz

    (Marmara University)

  • Özlem Şenvar

    (Marmara University)

  • İrem Ünal

    (Marmara University)

  • Serol Bulkan

    (Marmara University)

Abstract

Flexible job shop scheduling problem is a relaxation of the job shop scheduling problem and is one of the well-known combinatorial optimization problems that has wide applications in the industrial fields such as production management, supply chain, transport systems, manufacturing systems. In recent years, many researches have been carried out with different approaches—ranging from mathematical models to heuristic methods—to solve multi objective flexible job shop scheduling problems (FJSSP). This study aims to present the forms of scrutiny of multi-objective FJSSPs and various heuristic techniques used to solve problems in the last decade. This review will allow the reader to select specific methods and follow the guidelines set forth in their future research.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:joinma:v:31:y:2020:i:8:d:10.1007_s10845-020-01547-4
    DOI: 10.1007/s10845-020-01547-4
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    References listed on IDEAS

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    Cited by:

    1. Junqi Liu & Zeqiang Zhang & Feng Chen & Silu Liu & Lixia Zhu, 2022. "A novel hybrid immune clonal selection algorithm for the constrained corridor allocation problem," Journal of Intelligent Manufacturing, Springer, vol. 33(4), pages 953-972, April.
    2. Shun Jia & Yang Yang & Shuyu Li & Shang Wang & Anbang Li & Wei Cai & Yang Liu & Jian Hao & Luoke Hu, 2024. "The Green Flexible Job-Shop Scheduling Problem Considering Cost, Carbon Emissions, and Customer Satisfaction under Time-of-Use Electricity Pricing," Sustainability, MDPI, vol. 16(6), pages 1-22, March.
    3. Neufeld, Janis S. & Schulz, Sven & Buscher, Udo, 2023. "A systematic review of multi-objective hybrid flow shop scheduling," European Journal of Operational Research, Elsevier, vol. 309(1), pages 1-23.
    4. Bezoui, Madani & Olteanu, Alexandru-Liviu & Sevaux, Marc, 2023. "Integrating preferences within multiobjective flexible job shop scheduling," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1079-1086.
    5. Zeynep Ceylan & Hakan Tozan & Serol Bulkan, 2021. "A coordinated scheduling problem for the supply chain in a flexible job shop machine environment," Operational Research, Springer, vol. 21(2), pages 875-900, June.
    6. Fernando José Gómez Paredes & Moacir Godinho Filho & Matthias Thürer & Nuno O. Fernandes & Charbel José Chiappeta Jabbour, 2022. "Factors for choosing production control systems in make-to-order shops: a systematic literature review," Journal of Intelligent Manufacturing, Springer, vol. 33(3), pages 639-674, March.
    7. Alejandro Vital-Soto & Mohammed Fazle Baki & Ahmed Azab, 2023. "A multi-objective mathematical model and evolutionary algorithm for the dual-resource flexible job-shop scheduling problem with sequencing flexibility," Flexible Services and Manufacturing Journal, Springer, vol. 35(3), pages 626-668, September.

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