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Binary fuzzy goal programming approach to single model straight and U-shaped assembly line balancing

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  • Kara, Yakup
  • Paksoy, Turan
  • Chang, Ching-Ter

Abstract

Assembly line balancing generally requires a set of acceptable solutions to the several conflicting objectives. In this study, a binary fuzzy goal programming approach is applied to assembly line balancing. Models for balancing straight and U-shaped assembly lines with fuzzy goals (the number of workstations and cycle time goals) are proposed. The binary fuzzy goal programming models are solved using the methodology introduced by Chang [Chang, C.T., 2007. Binary fuzzy goal programming. European Journal of Operational Research 180 (1), 29-37]. An illustrative example is presented to demonstrate the validity of the proposed models and to compare the performance of straight and U-shaped line configurations.

Suggested Citation

  • Kara, Yakup & Paksoy, Turan & Chang, Ching-Ter, 2009. "Binary fuzzy goal programming approach to single model straight and U-shaped assembly line balancing," European Journal of Operational Research, Elsevier, vol. 195(2), pages 335-347, June.
    • Handle: RePEc:eee:ejores:v:195:y:2009:i:2:p:335-347
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    References listed on IDEAS

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    1. F. Brian Talbot & James H. Patterson, 1984. "An Integer Programming Algorithm with Network Cuts for Solving the Assembly Line Balancing Problem," Management Science, INFORMS, vol. 30(1), pages 85-99, January.
    2. Chang, Ching-Ter, 2007. "Binary fuzzy goal programming," European Journal of Operational Research, Elsevier, vol. 180(1), pages 29-37, July.
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    5. Gokcen, Hadi & Erel, Erdal, 1997. "A goal programming approach to mixed-model assembly line balancing problem," International Journal of Production Economics, Elsevier, vol. 48(2), pages 177-185, January.
    6. Aase, Gerald R. & Olson, John R. & Schniederjans, Marc J., 2004. "U-shaped assembly line layouts and their impact on labor productivity: An experimental study," European Journal of Operational Research, Elsevier, vol. 156(3), pages 698-711, August.
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    Cited by:

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    2. Borodin, Valeria & Dolgui, Alexandre & Hnaien, Faicel & Labadie, Nacima, 2016. "Component replenishment planning for a single-level assembly system under random lead times: A chance constrained programming approach," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 79-86.
    3. M. H. Alavidoost & M. H. Fazel Zarandi & Mosahar Tarimoradi & Yaser Nemati, 2017. "Modified genetic algorithm for simple straight and U-shaped assembly line balancing with fuzzy processing times," Journal of Intelligent Manufacturing, Springer, vol. 28(2), pages 313-336, February.
    4. Battaïa, Olga & Dolgui, Alexandre, 2013. "A taxonomy of line balancing problems and their solutionapproaches," International Journal of Production Economics, Elsevier, vol. 142(2), pages 259-277.
    5. Shraga Shoval & Mahmoud Efatmaneshnik & Michael J. Ryan, 2017. "Assembly sequence planning for processes with heterogeneous reliabilities," International Journal of Production Research, Taylor & Francis Journals, vol. 55(10), pages 2806-2828, May.
    6. Abolfazl Jafari Asl & Maghsud Solimanpur & Ravi Shankar, 2019. "Multi-objective multi-model assembly line balancing problem: a quantitative study in engine manufacturing industry," OPSEARCH, Springer;Operational Research Society of India, vol. 56(3), pages 603-627, September.
    7. Masood Fathi & María Jesús à lvarez & Victoria Rodríguez, 2016. "A new heuristic-based bi-objective simulated annealing method for U-shaped assembly line balancing," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 10(2), pages 145-169.

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