Genetic algorithm approach for solving a cell formation problem in cellular manufacturing

被引:78
|
作者
Mahdavi, Iraj [1 ]
Paydar, Mohammad Mahdi [1 ]
Solimanpur, Maghsud [2 ]
Heidarzade, Armaghan [1 ,3 ]
机构
[1] Mazandaran Univ Sci & Technol, Dept Ind Engn, Babol Sar 4716695635, Iran
[2] Urmia Univ, Fac Engn, Orumiyeh, Iran
[3] Payame Noor Univ, Dept Ind, Sari, Iran
关键词
Cell formation; Cellular manufacturing; Mathematical model; Genetic algorithm; Group efficacy; NEURAL-NETWORK APPROACH; GROUP-TECHNOLOGY; CLUSTERING-ALGORITHM; PART-FAMILIES; DESIGN; ASSIGNMENT; MATRICES; SYSTEMS; ROUTES; MODEL;
D O I
10.1016/j.eswa.2008.07.054
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Cellular manufacturing (CM) is an industrial application of group technology concept. One of the problems encountered in the implementation of CM is the cell formation problem (CFP). The CFP attempted here is to group machines and parts in dedicated manufacturing cells so that the number of voids and exceptional elements in cells are minimized. The proposed model, with nonlinear terms and integer variables, cannot be solved for real sized problems efficiently due to its NP-hardness. To solve the model for real-sized applications, a genetic algorithm is proposed. Numerical examples show that the proposed method is efficient and effective in searching for optimal solutions. The results also indicate that the proposed approach performs well in terms of group efficacy compared to the well-known existing cell formation methods. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:6598 / 6604
页数:7
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