Imperialistic Competitive Algorithm for Solving a Dynamic Cell Formation Problem with Production Planning

Abstract

Cellular manufacturing system, an application of group technology, has been considered as an effective way to obtain productivity in a factory. For design of manufacturing cells, several mathematical models and various algorithms have been proposed in literature. However, most of algorithms and models have more or fewer drawbacks. A dynamic cell formation problem with production planning is considered in this paper, where the sum of costs consisting constant machine costs, variable machine costs, intra-inter movement costs, production planning costs and reconfiguration costs is to be minimized. Because this type of problem is Np-hard, evolutionary algorithms are applied. In this paper the Imperialistic Competitive Algorithm (ICA), which optimizes inspired by imperialistic competition, is used. ICA is compared with other well-known evolutionary algorithms, i.e. genetic algorithm (GA) and particle swarm optimization (PSO), to show its efficiency. The computational results show the considerable superiority of ICA compared with PSO and GA.