Optimizing the Number of Cells in a Cellular Manufacturing System

In this paper, the solution of a non-linear model of Cell Manufacturing (CM) in certain and dynamic conditions is studied, considering intracellular and extracellular costs, cell constructing costs, the cost of restoration and the cost of equipment transportation per distance travelled. Since the number of cells in each stage of production is important, by optimizing the number of cells, additional costs can be minimized. Therefore, the main objective of this study is to investigate the optimal number of cells located. Bio-geographical Based Optimization (BBO) algorithm is applied in the CM for the first time in the literature and the obtained results from this algorithm are compared with the results of well-known genetic algorithm. The results shows the good performance of genetic algorithm. Finally, the conclusion and future research are provided.