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Hybrid Genetic Algorithm for Machine-Component Cell Formation

Hybrid Genetic Algorithm for Machine-Component Cell Formation
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摘要 This paper considers machine-component cell formation problem of cellular manufacturing system. Since this problem comes under combinatorial category, development of a meta-heuristic is a must. In this paper, a hybrid genetic algorithm is presented. Normally, in genetic algorithm, the initial population is generated by random assignment of genes in each of the chromosomes. In this paper, the initial population is created using ideal seed heuristic. The proposed algorithm is compared with four other algorithms using 28 problems from literature. Through a completed factorial experiment, it is observed that the proposed algorithm outperforms the other algorithms in terms of grouping efficiency as well as grouping efficacy. This paper considers machine-component cell formation problem of cellular manufacturing system. Since this problem comes under combinatorial category, development of a meta-heuristic is a must. In this paper, a hybrid genetic algorithm is presented. Normally, in genetic algorithm, the initial population is generated by random assignment of genes in each of the chromosomes. In this paper, the initial population is created using ideal seed heuristic. The proposed algorithm is compared with four other algorithms using 28 problems from literature. Through a completed factorial experiment, it is observed that the proposed algorithm outperforms the other algorithms in terms of grouping efficiency as well as grouping efficacy.
出处 《Intelligent Information Management》 2015年第3期107-122,共16页 智能信息管理(英文)
关键词 Machine-Component Cells Genetic Algorithm GROUPING Efficiency GROUPING Efficacy Hungerian Method Machine-Component Cells Genetic Algorithm Grouping Efficiency Grouping Efficacy Hungerian Method
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