Modeling and Solving of a Bi-Criteria Scheduling Problem for a Cellular Manufacturing System with Sequence-Dependent Cell Setup Times

This paper presents a new, bi-criteria mixed-integer programming model for scheduling cells (part families) and parts within each cell in a manufacturing cellular system. The objective of this model is to minimize the makespan and inter-cell movements simultaneously, while considering sequence-dependent cell setup times. In the CMS design and planning, three main steps must be considered, namely cell formation (i.e., part families and machine grouping), inter and intra-cell layouts, and scheduling issue. Due to the NP-hardness of the proposed model and the scheduling problem in the CMS, a genetic algorithm (GA) as an efficient meta-heuristic method is proposed to solve such a hard problem. Finally, a number of test problems are solved to show the efficiency of the proposed GA and the related computational results are compared with the results obtained by the use of an optimization tool.