developing a multi-objective mathematical model for dynamic cellular manufacturing systems

this paper is in search of designing the cellular manufacturing systems (cmss) under dynamic and flexible environment. cm is proper for small-to-medium lot production environment that helps the companies to produce variable kind of productions with at least scraps. the most important benefits of cm are decline in material handling, reduction in work-in-process, reduction in set-up time, increment in flexibility, improved quality, and shorter lead time. in this research a multi-objective mixed integer model is presented that considers some real-world critical conditions same as costs of multi-period cell formation and production planning , human resource assignment to cells and balancing workload of cells. this model groups the parts and machines concurrently with labor assignment this study aims to 1) minimize various costs including reassignment cost of human resource, the batch inter-cell material handling cost, constant and variable cost of machines, relocation and purchase cost of machines, 2) minimize cell load variation and 3) maximize utilization rate of human resource. the model is complicate, so it is verified with lingo 8. 0. soft ware. since particle swarm optimization approach less than many other metaheuristic approaches have been applied to solve multi-objective cms problems so far, we utilize this method to solve our model. the results are presented at the last part.