A Stochastic Optimization Method for Solving the Machine-Part Cell Formation Problem

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.