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 wellknown 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.