A novel hybrid algorithm for manufacturing cell formation problem

Abstract

The cell formation problem is a crucial component of a cell production design in a manufacturing system. Problems related to the cell formation problem are complex NP-hard problems. The goal of the work is to design the algorithm for the cell formation problem that is more efficient then the best-known algorithms for the same problem. The strategy of the new approach is to use the specificities of the input instances to narrow down the feasible set, and thus increase the efficiency of the optimization process. In the dynamic production environment, efficacy is one of the most significant characteristics of the applied expert system. The result is, extensible hybrid algorithm that can be used to solve complex, multi-criteria optimization cell formation problems. The new algorithm produces solutions that are as good as, or better than, the best results previously reported in literature on all commonly used test instances. The time efficiency of the proposed algorithm is at least an order of magnitude better than the efficiency of the most efficient reported algorithms. The obtained experimental results, modularity and generality of the new algorithm imply the significant impact on the expert systems for cell formation problem since the proposed strategy can improve the efficiency of existing algorithms for the grouping problems.