Title :
A PSO-Based Clustering Algorithm for Manufacturing Cell Design
Author :
Durán, Orlando ; Rodriguez, Nibaldo ; Consalter, Luiz Airton
Author_Institution :
Pontificia Univ. Catolica de Valparaiso, Valparaiso
Abstract :
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.
Keywords :
cellular manufacturing; design; minimisation; particle swarm optimisation; pattern clustering; clustering algorithm; inter-cell movements; machine grouping; manufacturing cell design; manufacturing cell formation; metaheuristic methods; particle swarm optimisation algorithm; proportional likelihood; Algorithm design and analysis; Cellular manufacturing; Clustering algorithms; Computational modeling; Data mining; Evolutionary computation; Group technology; Load management; Particle swarm optimization; Pulp manufacturing;
Conference_Titel :
Knowledge Discovery and Data Mining, 2008. WKDD 2008. First International Workshop on
Conference_Location :
Adelaide, SA
Print_ISBN :
978-0-7695-3090-1
DOI :
10.1109/WKDD.2008.1