Abstract
Cellular manufacturing system (CMS) involves a number of machine cells, where each cell is responsible for the processing of families of similar parts. The dynamic cellular manufacturing environment refers to anticipated changes of demand or production process for multiple time periods. This paper applied with the meta-heuristics for the design of Dynamic Cellular Manufacturing System (DCMS) using genetic algorithm (GA) to minimize holding cost, back order cost, machine cost and salary cost. It is shown that the PSO algorithm is efficient in finding out good quality solutions for the cellular manufacturing in a dynamic environment.
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