A multi-objective scatter search for a dynamic cell formation problem

被引：66

作者：

Bajestani, M. Aramoon ^{[1
]}

Rabbani, M. ^{[1
]}

Rahimi-Vahed, A. R. ^{[1
]}

Khoshkhou, G. Baharian ^{[1
]}

机构：

[1] Univ Tehran, Dept Ind Engn, Tehran 4563, Iran

来源：

COMPUTERS & OPERATIONS RESEARCH | 2009年 / 36卷 / 03期

关键词：

Multi-objective cell formation problem; Dynamic cell formation; Multi-objective scatter search; Multi-objective genetic algorithms; GENETIC-ALGORITHM; MANUFACTURING SYSTEMS; DESIGN; MODEL;

D O I：

10.1016/j.cor.2007.10.026

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Cellular manufacturing system-an important application of group technology (GT)-has been recognized as an effective way to enhance the productivity in a factory. Consequently, a multi-objective dynamic cell formation problem is presented in this paper, where the total cell load variation and sum of the miscellaneous costs (machine cost, inter-cell material handling cost, and machine relocation cost) are to he minimized simultaneously. Since this type of problem is NP-hard. a new multi-objective scatter search (MOSS) is designed for finding locally Pareto-optimal frontier. To demonstrate the efficiency of the proposed algorithm, MOSS is compared with two salient multi-objective genetic algorithms, i.e. SPEA-II and NSGA-II based on some comparison metrics and statistical approach. The computational results indicate the superiority of the proposed MOSS compared to these two genetic algorithms. (C) 2007 Elsevier Ltd. All rights reserved.

引用

页码：777 / 794

页数：18

共 40 条

[11] Machine cell formation using a mathematical model and a genetic-algorithm-based heuristic [J].