A genetic algorithm approach to the machine-component grouping problem with multiple objectives
Computers and Industrial Engineering
A tabu search approach to the cell formation problem
Computers and Industrial Engineering
Cell formation in group technology: review, evaluation and directions for future research
Computers and Industrial Engineering - Cellular manufacturing systems: design, analysis and implementation
A new discrete particle swarm algorithm applied to attribute selection in a bioinformatics data set
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Hi-index | 0.00 |
Since the last years different metaheuristic methods have been used to solve clustering problems. This paper addresses the problem of manufacturing Cell Formation using a modified particle swarm optimisation (PSO) algorithm. The main modification made to the original PSO algorithm consists on that in this work it is not used the vector of velocities as the standard PSO algorithm does. The proposed algorithm uses the concept of proportional likelihood with modifications, a technique that is used in data mining techniques. Some simulations are presented and compared. The criterion used to group the machines in cells is based on the minimization of inter-cell movements. The computational results show that the PSO algorithm is able to find the optimal solutions on almost all instances.