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An effective artificial fish swarm optimization algorithm for two-sided assembly line balancing problems

COMPUTERS & INDUSTRIAL ENGINEERING 2019年 138卷 106121-000页

作者： Zhong, Yuguang Deng, Zexiao Xu, Ke Harbin Engn Univ Coll Mech & Elect Engn Harbin 150001 Heilongjiang Peoples R China

Two-sided assembly lines are often used in assembly of large-sized products, such as automobiles, buses and trucks. Compared to the traditional one-sided assembly line, two-sided assembly line has advantages of shorter line and higher utilization of fixture. However, normal balancing method is not applicable to solve the two-sided assembly line balancing problem since the constraint conditions become more complicated. On the other hand, artificial fish swarm algorithm is a relatively new member of swarm intelligence based on swarm behaviors that were inspired from social behaviors of fish swarm in nature. As a typical application of behaviorism in artificial intelligence, artificial fish swarm algorithm can search for the global optimum. So it is a good candidate for developing new search algorithm for solving optimization problems in operational research. In this research, an effective discrete artificial fish swarm algorithm is developed to solve the cost-oriented assembly line balancing problems which aims to minimize the construction cost and at the same time minimize the number of matestation. Through extensive computational experiments, the performance of the proposed artificial fish swarm algorithm is examined. The experimental results validate the effectiveness and efficiency of the proposed method.

关键词： Fish swarm algorithm Two-sided assembly line Assembly line balancing optimization computing

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