Modeling the Scheduling Problem in Cellular Manufacturing Systems Using Genetic Algorithm as an Efficient Meta-Heuristic Approach

Abstract

This paper presents a new, bi-criteria mixed-integer programming model for scheduling cells and pieces within each cell in a manufacturing cellular system. The objective of this model is to minimize the makespan and intercell movements simultaneously, while considering sequence-dependent cell setup times. In the cellular manufacturing systems design and planning, three main steps must be considered, namely cell formation (i.e., piece families and machine grouping), inter and intracell layouts, and scheduling issue. Due to the fact that the cellular manufacturing systems problem is NP-Hard, a genetic algorithm 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 genetic algorithm and the related computational results are compared with the results obtained by the use of an optimization tool.