A multi-objective genetic algorithm for solving cell formation problem using a fuzzy goal programming approach

被引：14

作者：

Saeidi, Shahram ^{[1
]}

Solimanpur, Maghsud ^{[2
]}

Mahdavi, Iraj ^{[3
]}

Javadian, Nikbakhsh ^{[3
]}

机构：

[1] Islamic Azad Univ, Tabriz Branch, Dept Comp Engn, Tabriz, Iran

[2] Urmia Univ, Fac Engn, Orumiyeh, West Azerbaijan, Iran

[3] Mazandaran Univ Sci & Technol, Dept Ind Engn, Babol Sar, Iran

来源：

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY | 2014年 / 70卷 / 9-12期

关键词：

Cell formation problem; Cellular manufacturing; Group technology; Fuzzy goal programming; Genetic algorithm; NSGA-II; SWARM OPTIMIZATION APPROACH; MANUFACTURING SYSTEMS; DESIGN OPTIMIZATION; IMMUNE ALGORITHM; TABU SEARCH; LAYOUT;

D O I：

10.1007/s00170-013-5392-0

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A comprehensive multi-objective mathematical programming model is proposed in this paper to design a cellular manufacturing system. The model considers machine redundancy, production volume, processing time, cost of machines, sequence of operations, and alternative processing plans. A fuzzy goal programming approach is used to convert the proposed multi-objective model into a single-objective one. Due to NP-hard nature of the model, a genetic algorithm is developed for solving the proposed model. Performance of the proposed genetic algorithm is evaluated by adopting four problems from literature. The results indicate effectiveness and efficiency of the proposed algorithm in comparison with those obtained by Lingo and NSGA-II algorithm.

引用

页码：1635 / 1652

页数：18

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