A genetic algorithm approach for a dynamic cell formation problem considering machine breakdown and buffer storage

Cell formation problem mainly address how machines should be grouped and parts be processed in cells. In dynamic environments, product mix and demand change in each period of the planning horizon. Incorporating such assumption in the model increases flexibility of the system to meet customer’s requirements. In this model, to ensure the reliability of the system in presence of unreliable machines, alternative routing process as well as buffer storage is considered to reduce detrimental effects of machine failure. This problem is presented by a nonlinear mixed integer programming model attempting to minimize the overall cost of the system. To solve the model in large scale for practical purposes, a genetic algorithm approach is adopted as the model belongs to NP-hard class of problem. A numerical example is used both, for small-sized and large-sized instances to show the validity and efficiency of the method in finding near optimal solution.