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Solving a bi-objective mixed-model assembly-line sequencing using metaheuristic algorithms considering ergonomic factors, customer behavior, and periodic maintenance

Author

Listed:
  • Masoud Rabbani

    (University of Tehran)

  • Mahdi Mokhtarzadeh

    (University of Tehran)

  • Neda Manavizadeh

    (KHATAM University)

  • Azadeh Farsi

    (University of Tehran)

Abstract

In today’s competitive world, companies must maintain their customers and attract new ones. Hence, they paid a great attention paid to mixed model assembly lines (MMAL). In this study, a two-step framework was developed to investigate and optimize customer relationships and the sequence of orders in an MMAL. First, based on customers past behavior, they were grouped into three clusters with high, normal, and low priority. Then, an optimal sequence was defined using a mathematical model. The objectives of the sequence were maximizing, first, the satisfaction of customers with high priority and, second, profits. Moreover, orders for low priority customers could be rejected. A multi-objective tabu search algorithm was proposed to solve the sequencing problem and then compared with non-dominated sorting genetic algorithm II and multi objective simulated annealing. The results indicated that this new algorithm is superior to others. We also developed an algorithm for the integration of periodic maintenance with sequencing of orders. The results suggested that the lack of this integration causes non-optimal sequences.

Suggested Citation

  • Masoud Rabbani & Mahdi Mokhtarzadeh & Neda Manavizadeh & Azadeh Farsi, 2021. "Solving a bi-objective mixed-model assembly-line sequencing using metaheuristic algorithms considering ergonomic factors, customer behavior, and periodic maintenance," OPSEARCH, Springer;Operational Research Society of India, vol. 58(3), pages 513-539, September.
    • Handle: RePEc:spr:opsear:v:58:y:2021:i:3:d:10.1007_s12597-020-00489-y
    DOI: 10.1007/s12597-020-00489-y
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    References listed on IDEAS

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    1. Fred Glover, 1989. "Tabu Search---Part I," INFORMS Journal on Computing, INFORMS, vol. 1(3), pages 190-206, August.
    2. Pâmela M.C. Cortez & Alysson M. Costa, 2015. "Sequencing mixed-model assembly lines operating with a heterogeneous workforce," International Journal of Production Research, Taylor & Francis Journals, vol. 53(11), pages 3419-3432, June.
    3. Baoxi Wang & Zailin Guan & Saif Ullah & Xianhao Xu & Zongdong He, 2017. "Simultaneous order scheduling and mixed-model sequencing in assemble-to-order production environment: a multi-objective hybrid artificial bee colony algorithm," Journal of Intelligent Manufacturing, Springer, vol. 28(2), pages 419-436, February.
    4. Akyildiz, Burcu & Kadaifci, Cigdem & Topcu, Ilker, 2015. "A decision framework proposal for customer order prioritization: A case study for a structural steel company," International Journal of Production Economics, Elsevier, vol. 169(C), pages 21-30.
    5. Boysen, Nils & Fliedner, Malte & Scholl, Armin, 2008. "Assembly line balancing: Which model to use when," International Journal of Production Economics, Elsevier, vol. 111(2), pages 509-528, February.
    6. Parames Chutima & Sathaporn Olarnviwatchai, 2018. "A multi-objective car sequencing problem on two-sided assembly lines," Journal of Intelligent Manufacturing, Springer, vol. 29(7), pages 1617-1636, October.
    7. Ivan Kristianto Singgih & Onyu Yu & Byung-In Kim & Jeongin Koo & Seungdoe Lee, 2020. "Production scheduling problem in a factory of automobile component primer painting," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1483-1496, August.
    8. Boysen, Nils & Fliedner, Malte & Scholl, Armin, 2009. "Sequencing mixed-model assembly lines: Survey, classification and model critique," European Journal of Operational Research, Elsevier, vol. 192(2), pages 349-373, January.
    9. H. Mosadegh & S.M.T. Fatemi Ghomi & G.A. Süer, 2017. "Heuristic approaches for mixed-model sequencing problem with stochastic processing times," International Journal of Production Research, Taylor & Francis Journals, vol. 55(10), pages 2857-2880, May.
    10. Xiaoyi Deng, 2013. "An Efficient Hybrid Artificial Bee Colony Algorithm for Customer Segmentation in Mobile E-commerce," Journal of Electronic Commerce in Organizations (JECO), IGI Global, vol. 11(2), pages 53-63, April.
    11. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    12. Fred Glover, 1990. "Tabu Search—Part II," INFORMS Journal on Computing, INFORMS, vol. 2(1), pages 4-32, February.
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