A metaheuristic approach for a cubic cell formation problem

The minimizations of voids and exceptional elements by considering the part-machine incidence matrix of the cell formation problem have been discussed in the literature. In recent years, a few mathematical models considering the assignment of workers to cells in addition to part and machine have been proposed to fully utilize manufacturing systems. Although the proposed mathematical models can produce the best solutions for small sized problems within reasonable times, they are inadequate to produce the best solutions for large sized real life cases due to the NP-hard nature of the problem. In this study, a genetic algorithm has been proposed for the problem of part-machine-worker cell formation. Furthermore, the Taguchi method, as a statistical optimization technique, has been used to determine the appropriate levels of the parameters. The performance of the proposed genetic algorithm has been tested using test data from the literature for small sized problems and using data that was generated in this study for large sized problems. The experimental results of this study show that the proposed genetic algorithm can produce the optimal solutions for small sized problems and that the proposed algorithm can yield optimal or near-optimal solutions for large sized problems within reasonable times.