Modeling the Scheduling Problem in Cellular Manufacturing Systems Using Genetic Algorithm as an Efficient Meta-Heuristic Approach

Amin Rezaeipanah; Musa Mojarad

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Modeling the Scheduling Problem in Cellular Manufacturing Systems Using Genetic Algorithm as an Efficient Meta-Heuristic Approach

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This paper presents a new,bi-criteria mixed_integer programming model for scheduling cells and pieces within each cell in a manufacturing cellular system.The objective of this model is to minimize the makespan and intercell movements simultaneously,while considering sequence-dependent cell setup times.In the cellular manufacturing systems design and planning,three main steps must be considered,namely cell formation(i.e,piece families and machine grouping),inter and intra-cell layouts,and scheduling issue.Due to the fact that the cellular manufacturing systems problem is NP-Hard,a genetic algorithm as an efficient meta-heuristic method is proposed to solve such a hard problem.Finally,a number of test problems are solved to show the efficiency of the proposed genetic algorithm and the related computational results are compared with the results obtained by the use of an optimization tool.

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《人工智能技术学报（英文）》 |2021年第4期|228-234|共7页
作者
Amin Rezaeipanah; Musa Mojarad;
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作者单位

Depiecement of Computer Engineering;

University of Rahjuyan Danesh Borazjan;

Bushehr;

Iran;

Depiecement of Computer Engineering;

Firoozabad Branch;

Islamic Azad University;

Firoozabad;

Iran;

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原文格式 PDF
正文语种 chi
中图分类计算技术、计算机技术;
关键词
scheduling; cellular manufacturing system; genetic algorithm; meta-heuristic;

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Modeling the Scheduling Problem in Cellular Manufacturing Systems Using Genetic Algorithm as an Efficient Meta-Heuristic Approach

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