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Erschienen in:
2006 | OriginalPaper | Buchkapitel
Improving the Genetic Algorithms Performance in Simple Assembly Line Balancing
verfasst von : Seren Özmehmet Tasan, Semra Tunali
Erschienen in: Computational Science and Its Applications - ICCSA 2006
Verlag: Springer Berlin Heidelberg
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In this paper, a hybrid GA approach combining genetic algorithm (GA) and tabu search (TS) is proposed to solve simple assembly line balancing problem. As this problem is combinatorial and NP hard in nature, the optimum seeking methods are impractical. Therefore, we proposed a hybrid approach, which unites the advantages and mitigates the disadvantages of the two algorithms. To increase the performance of the hybrid GA, we also optimized the control parameters such as the population size, rate of crossover and mutation. Moreover, to gain more insight on the performance of hybrid GA, we implemented it to various benchmark problems and observed that the hybridization of GA with TS improves the solution performance of the balancing problem.