First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008)
A PSO-Based Clustering Algorithm for Manufacturing Cell Design
Adelaide, Australia
January 23-January 24
ISBN: 0-7695-3090-7
DOI Bookmark:
http://doi.ieeecomputersociety.org/10.1109/WKDD.2008.1
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: Manufacturing cells, machine grouping, particle swarm optimization I.
Citation:
Orlando Duran, Nibaldo Rodriguez, Luiz Airton Consalter, "A PSO-Based Clustering Algorithm for Manufacturing Cell Design," wkdd, pp.72-75, First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008), 2008
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