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A hybrid multi-objective genetic algorithm based on the ELECTRE method for a capacitated flexible job shop scheduling problem

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Abstract

In this paper, a multi-objective flexible job shop scheduling problem with machines capacity constraints is studied. Minimizing the makespan and overtime costs of machines are considered as two objectives for evaluating solutions. First, a new nonlinear integer programming model is presented to formulate the problem. Inasmuch as this problem is well-known as a NP-hard problem, a hybrid meta-heuristic algorithm (CFJSP II) is developed to overcome its complexity. Regarding to the solution space of the problem, for assigning and sequencing operations, a multi-objective genetic algorithm based on the ELECTRE method is presented. Also, a powerful heuristic approach to tradeoff the objective functions is developed. Finally, the proposed algorithm is compared with some well-known multi-objective algorithms such as NSGAII, SPEA2, and VEGA. Regarding to the computational results, it is clear that the proposed algorithm has a better performance especially in the closeness of the solutions to the Pareto optimal front.

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Authors and Affiliations

  1. Department of Industrial Engineering, Bu-Ali Sina University, Hamedan, Iran

    Mohamad Rohaninejad, Amirsaman Kheirkhah, Parviz Fattahi & Behdin Vahedi-Nouri

Authors
  1. Mohamad Rohaninejad
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  2. Amirsaman Kheirkhah
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  3. Parviz Fattahi
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  4. Behdin Vahedi-Nouri
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Correspondence to Parviz Fattahi.

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Rohaninejad, M., Kheirkhah, A., Fattahi, P. et al. A hybrid multi-objective genetic algorithm based on the ELECTRE method for a capacitated flexible job shop scheduling problem. Int J Adv Manuf Technol 77, 51–66 (2015). https://doi.org/10.1007/s00170-014-6415-1

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  • DOI: https://doi.org/10.1007/s00170-014-6415-1

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