Journal Article10.1080/07408179608966253
Manufacturing cell design: an integer programming model employing genetic algorithms
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TL;DR: In this article, an integer program that is solved using a GA to assist in the design of cellular manufacturing systems is presented, where a unique representation scheme for individuals (part/machine partitions) is used to reduce the size of the cell formation problem and increase the scale of problems that can be solved.
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Abstract: The design of a cellular manufacturing system requires that a part population, at least minimally described by its use of process technology (part/machine incidence matrix), be partitioned into part families and that the associated plant equipment be partitioned into machine cells. At the highest level, the objective is to form a set of completely autonomous units such that inter-cell movement of parts is minimized. We present an integer program that is solved using a genetic algorithm (GA) to assist in the design of cellular manufacturing systems. The formulation uses a unique representation scheme for individuals (part/machine partitions) that reduces the size of the cell formation problem and increases the scale of problems that can be solved. This approach offers improved design flexibility by allowing a variety of evaluation functions to be employed and by incorporating design constraints during cell formation. The effectiveness of the GA approach is demonstrated on several problems from the literature.
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