A Genetic Algorithm Approach for Solving Group Technology Problem with Process Plan Flexibility

A more and more competitive environment and constantly changing customers' favors have forced producers to enhance quality, efficiency and flexibility. The cellular manufacturing system (CMS) which is a manufacturing application of the group technology (GT) theory, has been known as one of the recent technological innovations for providing more productivity and flexibility. Different aspects of CMS have been continuously investigated in the recent years. In the previous studies, minimizing the total number of intercellular movement or exceptional parts has been considered as an objective. In this paper, a multi-objective mathematical model for solving the group technology problem with process route flexibility has been developed and described. The objective functions are minimizing the total intercellular movement, machines' idle time and the total required setup time while satisfying a number of constraints. A solver based on genetic algorithm (GA) has been created and validated using the Visual Studio C# programming language. Finally, the created software has been utilized to solve the cell formation problem (CFP) in an industrial case company.