A genetic algorithm for solving integrated cell formation and layout problem considering alternative routings and machine capacities

In this paper an integrated approach was presented to simultaneously solve the cell formation and its layout problems. Many real world parameters such as part demands, alternative processing routings, machine capacities, cell dimensions, multi-rows arrangement of machines within the cells, aisle distances, etc., were considered in this approach, to make the problem more realistic. Also, in order to measure the material handling cost more precisely, the actual position of machines within the cells was used (instead of the center-to-center distances between the cells). Due to the complexity of the proposed problem a genetic algorithm was developed to efficiently solve it in a reasonable computational time. Finally, the performance of the genetic algorithm was evaluated by solving several numerical examples from the literature. The results revealed that when the decisions about the cell formation, inter and intra-cell layouts and routing of parts are simultaneously made the total material handling cost may reduce significantly in comparison with the sequential design approach.