Mixed-Model Parallel U-Shaped Assembly Line Balancing under Many-Objectives Using a Multi-Objective Evolutionary Algorithm Based on Decomposition
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Published:
Aug 20, 2018
Keywords:
Parallel U-shaped assembly line line balancing many objective optimization problem multi objective evolutionary algorithm based on decomposition
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Abstract
Mixed-Model Parallel U-shaped assembly line balancing problem under many-Objectives is known as NP-hard problems. Hence, to optimize this problem, heuristic approaches need to be developed. This research proposes a decode method and a Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D) for solving the problem by optimizing four objectives simultaneously, i.e. minimize the number of workstations, minimize the number of stations, minimize different workload between workstations, and minimize work unrelatedness. The experiment results show that MOEA/D has better performance than BBO in terms of convergence. However, its spread and CPU time indicators are not better than BBO.
Article Details
How to Cite
[1]
ชุติมา ป., “Mixed-Model Parallel U-Shaped Assembly Line Balancing under Many-Objectives Using a Multi-Objective Evolutionary Algorithm Based on Decomposition”, sej, vol. 13, no. 1, pp. 82–97, Aug. 2018.
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Research Articles
Copyright belongs to Srinakharinwirot University Engineering Journal
References
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[19] วัชรวิทย์ ถนนทอง, "การจัดลำดับผลิตรถยนต์แบบหลายวัตถุประสงค์บนสายการประกอบผลิตภัณฑ์ผสมแบบสองด้านด้วยอัลกอริทึมการบรรจวบร่วมกับฟัซซี่," วิทยานิพนธ์วิศวกรรมศาสตรมหาบัณฑิต, ภาควิชาวิศวกรรมอุตสาหการ, จุฬาลงกรณ์มหาวิทยาลัย, 2558.
[2] I. Kucukkoc and D. Z. Zhang, "Balancing of parallel U-shaped assembly lines," Computers & OR, vol. 64, pp. 233-244, 2015.
[3] ณัฐชัย โยธาบริบาร, "การจัดสมดุลที่มีหลายวัตถุประสงค์บนสายการประกอบผลิตภัณฑ์ผสมแบบ ขนาน ด้วยอัลกอริทึมแบบการกระจายตัวของสิ่งมีชีวิตตามภูมิศาสตร์," วิทยานิพนธ์วิศวกรรมศาสตรมหาบัณฑิต, ภาควิชาวิศวกรรมอุตสาหการ, จุฬาลงกรณ์มหาวิทยาลัย, 2556.
[4] C. Becker and A. Scholl, "A survey on problems and methods in generalized assembly line balancing," Eur. J. Oper. Res., vol. 168, no. 3, pp. 694-715, 2006.
[5] Q. Zhang and H. Li, "MOEA/D: A multiobjective evolutionary algorithm based on decomposition," IEEE Trans. Evol. Comput., vol. 11, no. 6, pp. 712-731, 2007.
[6] R. Cheng et al., "A benchmark test suite for evolutionary many-objective optimization," Complex Intell. Syst., vol. 3, no. 1, pp. 67-81, 2017.
[7] D. Simon, "Biogeography-based optimization," IEEE Trans. Evol. Comput., vol. 12, no. 6, pp. 702-713, 2008.
[8] J. L. C. Macaskill, "Production-line balances for mixed-model lines," Manage. Sci., vol. 19, no. 4-part-1, pp. 423-434, 1972.
[9] D. Sparling and J. Miltenburg, "The mixed-model u-line balancing problem," Int. J. Prod. Res., vol. 36, no. 2, pp. 485-501, 1998.
[10] Y. K. Kim, Y. Kim, and Y. J. Kim, "Two-sided assembly line balancing: A genetic algorithm approach," Prod. Plann. Contr., vol. 11, no. 1, pp. 44-53, 2000.
[11] P. M. Vilarinho and A. S. Simaria, "A two-stage heuristic method for balancing mixed-model assembly lines with parallel workstations," Int. J. Prod. Res., vol. 40, no. 6, pp. 1405-1420, 2002.
[12] T. O. Lee, Y. Kim, and Y. K. Kim, "Two-sided assembly line balancing to maximize work relatedness and slackness," Comput. Ind. Eng., vol. 40, no. 3, pp. 273-292, 2001.
[13] D. E. Goldberg and R. Lingle, "Alleles, loci, and the traveling salesman problem,"An international conference on genetic algorithms and their applications, 1985, vol. 154, pp. 154-159: Lawrence Erlbaum, Hillsdale, NJ.
[14] R. K. Hwang, H. Katayama, and M. Gen, "U-shaped assembly line balancing problem with genetic algorithm," Int. J. of Prod. Res., vol. 46, no. 16, pp. 4637-4649, 2008.
[15] H. Ma, "An analysis of the equilibrium of migration models for biogeography-based optimization," Inform. Sci., vol. 180, no. 18, pp. 3444-3464, 2010.
[16] Y. K. Kim, C. J. Hyun, and Y. Kim, "Sequencing in mixed model assembly lines: a genetic algorithm approach," Computers & OR, vol. 23, no. 12, pp. 1131-1145, 1996.
[17] K. JitmettaI, "Application of particle swarm optimization for multi-objective sequencing problems on mixed-model two-sided assembly lines," M.S. thesis, Dept. Ind. Eng., Chulalongkorn University, 2011.
[18] R. Kumar and P. K. Singh, "Pareto Evolutionary Algorithm Hybridized with Local Search for Biobjective TSP," in Hybrid Evolutionary Algorithms, A. Abraham, C. Grosan, and H. Ishibuchi, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007, pp. 361-398.
[19] วัชรวิทย์ ถนนทอง, "การจัดลำดับผลิตรถยนต์แบบหลายวัตถุประสงค์บนสายการประกอบผลิตภัณฑ์ผสมแบบสองด้านด้วยอัลกอริทึมการบรรจวบร่วมกับฟัซซี่," วิทยานิพนธ์วิศวกรรมศาสตรมหาบัณฑิต, ภาควิชาวิศวกรรมอุตสาหการ, จุฬาลงกรณ์มหาวิทยาลัย, 2558.