A new solution for a dynamic cell formation problem with alternative routing and machine costs using simulated annealing

This paper presents an integer-linear programming approach for a cell formation problem (CFP) in a dynamic environment with a multi-period planning horizon. The objectives are to minimize the inter-cell movement and machine costs simultaneously. In dynamic environments, the product mix and demand are different but deterministic in each period. As a consequence, the formed cells in the current period may not be optimal for the next period. Thus, the reconfiguration of cells is required. Reconfiguration consists of re-forming part families, machine groups, and machine relocation. The CFP belongs to the category of NP-hard problems, thus we develop an efficient simulated annealing (SA) method to solve such a problem.