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 layout problems. Design parameters, such as part demands, alternative process routings, machine capacities, cell dimensions, multi-row arrangement of machines within cells, aisle distances, etc. were considered in this approach to make it more realistic. Also, in order to measure the material handling cost more precisely, the actual position of the 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 indicated that when decisions about cell formation, inter and intra-cell layouts and routing of parts are simultaneously made, the total material handling costs may reduce significantly in comparison with the sequential design approach. (C) 2014 Sharif University of Technology. All rights reserved.