A particle Swarm Optimization algorithm for Part-Machine grouping

摘要

This paper presents a particle swarm optimization (PSO) algorithm to address the cell formation problem in Group Technology. As it is well known, machine-part group formation is an important issue in the design of cellular manufacturing systems. In the last years some metaheuristics have been used to solve this problem, but this is the first time that a PSO algorithm is used to solve it. PSO is a recent parallel evolutionary computation technique based on the social behaviour metaphor. The approach used to group the machines in cells is based on the minimization of inter cell movements. We used exact results as benchmarks to compare our algorithm. The computational results show that PSO algorithm is able to find the optimal solutions on almost all instances.