In this paper, we study the machine-part cell formation problem. The problem is to assign the given machines and parts into cells so that the grouping efficacy, a measure of autonomy, is maximized. First, we introduce a new randomized local search algorithm which requires solving another subproblem for assigning optimally parts into cells on the basis of given groups of machines. Second, we propose an exact, polynomial-time algorithm to solve this subproblem. Finally, we provide the numerical results of our proposed algorithm, using a popular set of benchmark problems. Comparisons with other recent algorithms in the literature show that our algorithm can improve the current best-known solutions for some instances. © 2011 Springer-Verlag.
CITATION STYLE
Trinh, K., Ferland, J., & Dinh, T. (2011). A stochastic optimization method for solving the machine-part cell formation problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6838 LNCS, pp. 162–169). https://doi.org/10.1007/978-3-642-24728-6_22
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