Mixed-Model Parallel U-Shaped Assembly Line Balancing under Many-Objectives Using a Multi-Objective Evolutionary Algorithm Based on Decomposition

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ปารเมศ ชุติมา


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.

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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.
Research Articles


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