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Integrating preferences within multiobjective flexible job shop scheduling

Author

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  • Bezoui, Madani
  • Olteanu, Alexandru-Liviu
  • Sevaux, Marc

Abstract

When faced with a multiobjective optimization problem, it is necessary to consider the decision-maker preferences in order to propose the best compromise solution. We consider the multiobjective flexible job shop scheduling problem and a decision-maker that is best represented using a non-compensatory reference level-based preference model. We show how integrating this model into a multiobjective genetic algorithm allows to obtain solutions that surpass more aspiration levels when compared to classical multiobjective optimization approaches. Furthermore, these solutions are found faster and in greater numbers which facilitates their integration within the workshop.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:305:y:2023:i:3:p:1079-1086
    DOI: 10.1016/j.ejor.2022.07.002
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    References listed on IDEAS

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    4. 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.
    5. Alexandru-Liviu Olteanu & Khaled Belahcene & Vincent Mousseau & Wassila Ouerdane & Antoine Rolland & Jun Zheng, 2022. "Preference elicitation for a ranking method based on multiple reference profiles," 4OR, Springer, vol. 20(1), pages 63-84, March.
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