A hybrid grouping genetic algorithm for the cell formation problem

被引:113
|
作者
James, Tabitha L. [1 ]
Brown, Evelyn C. [1 ]
Keeling, Kellie B. [1 ]
机构
[1] Virginia Polytech Inst & State Univ, RB Pamplin Coll Business, Dept Business Informat Technol, Blacksburg, VA 24061 USA
关键词
machine-part cell formation; grouping genetic algorithm; heuristics;
D O I
10.1016/j.cor.2005.08.010
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The machine-part cell formation problem consists of constructing a set of machine cells and their corresponding product families with the objective of minimizing the inter-cell movement of the products while maximizing machine utilization. This paper presents a hybrid grouping genetic algorithm for the cell formation problem that combines a local search with a standard grouping genetic algorithm to form machine-part cells. Computational results using the grouping efficacy measure for a set of cell formation problems from the literature are presented. The hybrid grouping genetic algorithm is shown to outperform the standard grouping genetic algorithm by exceeding the solution quality on all test problems and by reducing the variability among the solutions found. The algorithm developed performs well on all test problems, exceeding or matching the solution quality of the results presented in previous literature for most problems. (c) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码:2059 / 2079
页数:21
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