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Mixed-product flexible assembly line balancing based on a genetic algorithm  

Song Won Seop (전남대학교 산업공학과)
Kim Hyeong Su (전남대학교 산업공학과)
Kim Yeo Keun (전남대학교 산업공학과)
Publication Information
Journal of the Korean Operations Research and Management Science Society / v.30, no.1, 2005 , pp. 43-54 More about this Journal
Abstract
A flexible assembly line (FAL) is a production system that assembles various parts in unidirectional flow line with many constraints and manufacturing flexibilities. In this research we deal with a FAL balancing problem with the objective of minimizing the maximum workload allocated to the stations. However, almost all the existing researches do not appropriately consider various constraints due to the problem complexity. Therefore, this study addresses a balancing problem of FAL with many constraints and manufacturing flexibilities, unlike the previous researches. We use a genetic algorithm (GA) to solve this problem. To apply GA to FAL. we suggest a genetic representation suitable for FAL balancing and devise evaluation method for individual's fitness and genetic operators specific to the problem, including efficient repair method for preserving solution feasibility. After we obtain a solution using the proposed GA. we use a heuristic method for reassigning some tasks of each product to one or more stations. This method can improve workload smoothness and raise work efficiency of each station. The proposed algorithm is compared and analyzed in terms of solution quality through computational experiments.
Keywords
Flexible Assembly Line; Line Balancing; Flexibility; Genetic Algorithm;
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