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Considering environmental impacts in flexible assembly job shop scheduling: non-dominated sorting memetic algorithm

Author

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  • M. Hajibabaei

    (Bu-Ali Sina University)

  • J. Behnamian

    (Bu-Ali Sina University)

Abstract

This paper studies the flexible assembly job shop scheduling problems with cleaner production criterion, interruption, and batch delivery. In this case, considering release time, the parts are produced in the first stage in a flexible job shop environment. In the second stage, they are assembled in the flowshop environment to produce the final products. After assembling, in the final stage, the products are sent to customers in batches. The objective function is to minimize the costs of tardiness, earliness, delivery, and maximum completion time, along with minimizing the amount of speed increase and carbon dioxide emissions. To make the problem more realistic, the fuzzy uncertainty is considered in the problem so that the cost of delivery and the amount of carbon dioxide emission are considered as a triangular fuzzy number. In this study, a mixed-integer nonlinear programming model has been developed to solve the used Epsilon-constraint method. Since the problem of flexible job shop scheduling is one of the most complex problems of combinatorial optimization, to solve it, a hybrid algorithm consisting of NSGAII and memetic is presented. To evaluate the performance of the proposed algorithm, according to some evaluation criteria, the proposed algorithm and NSGAII were compared, and the obtained results showed that the proposed algorithm has good performance.

Suggested Citation

  • M. Hajibabaei & J. Behnamian, 2025. "Considering environmental impacts in flexible assembly job shop scheduling: non-dominated sorting memetic algorithm," Flexible Services and Manufacturing Journal, Springer, vol. 37(2), pages 632-673, June.
    • Handle: RePEc:spr:flsman:v:37:y:2025:i:2:d:10.1007_s10696-024-09553-x
    DOI: 10.1007/s10696-024-09553-x
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    References listed on IDEAS

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    1. M. Hajibabaei & J. Behnamian, 2023. "Fuzzy cleaner production in assembly flexible job-shop scheduling with machine breakdown and batch transportation: Lagrangian relaxation," Journal of Combinatorial Optimization, Springer, vol. 45(5), pages 1-26, July.
    2. Xuran Gong & Qianwang Deng & Guiliang Gong & Wei Liu & Qinghua Ren, 2018. "A memetic algorithm for multi-objective flexible job-shop problem with worker flexibility," International Journal of Production Research, Taylor & Francis Journals, vol. 56(7), pages 2506-2522, April.
    3. Ahmadian, Mohammad Mahdi & Salehipour, Amir & Cheng, T.C.E., 2021. "A meta-heuristic to solve the just-in-time job-shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 288(1), pages 14-29.
    4. Shen, Liji & Dauzère-Pérès, Stéphane & Neufeld, Janis S., 2018. "Solving the flexible job shop scheduling problem with sequence-dependent setup times," European Journal of Operational Research, Elsevier, vol. 265(2), pages 503-516.
    5. Fei Shi & Shikui Zhao & Yue Meng, 2020. "Hybrid algorithm based on improved extended shifting bottleneck procedure and GA for assembly job shop scheduling problem," International Journal of Production Research, Taylor & Francis Journals, vol. 58(9), pages 2604-2625, May.
    6. Liyuan Zhang & Xuanhua Xu & Li Tao, 2013. "Some Similarity Measures for Triangular Fuzzy Number and Their Applications in Multiple Criteria Group Decision‐Making," Journal of Applied Mathematics, John Wiley & Sons, vol. 2013(1).
    7. Liyuan Zhang & Xuanhua Xu & Li Tao, 2013. "Some Similarity Measures for Triangular Fuzzy Number and Their Applications in Multiple Criteria Group Decision-Making," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-7, March.
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