Article ID: | iaor2013758 |
Volume: | 40 |
Issue: | 4 |
Start Page Number: | 980 |
End Page Number: | 990 |
Publication Date: | Apr 2013 |
Journal: | Computers and Operations Research |
Authors: | Paydar Mohammad Mahdi, Saidi-Mehrabad Mohammad |
Keywords: | heuristics, heuristics: genetic algorithms, production, combinatorial optimization |
Cell formation problem attempts to group machines and part families in dedicated manufacturing cells such that the number of voids and exceptional elements in cells are minimized. In this paper, we presented a linear fractional programming model with the objective of maximizing the grouping efficacy while the number of cells is unknown. To show the effectiveness of the proposed model, two test problems were applied. Then, to solve the model for real‐sized applications, a hybrid meta‐heuristic algorithm in which genetic algorithm and variable neighborhood search are combined. Using the grouping efficacy measure, we have also compared the performance of the proposed algorithm on a set of 35 test problems from the literature. The results show that the proposed GA‐VNS method outperforms the state‐of‐the‐art algorithms.