A PSO-based clustering algorithm for manufacturing cell design

Orlando Durán, Nibaldo Rodriguez, Luiz Airton Consalter

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicatione-Forensics 2008 - Proceedings of the 1st International Conference on Forensic Applications and Techniques in Telecommunications, Information, and Multimedia and Workshop
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9789639799196
DOIs
StatePublished - 21 Jan 2008
Event1st International Conference on Forensic Applications and Techniques in Telecommunications, Information, and Multimedia and Workshop, e-Forensics 2008 - Adelaide, Australia
Duration: 21 Jan 200823 Jan 2008

Publication series

Namee-Forensics 2008 - Proceedings of the 1st International Conference on Forensic Applications and Techniques in Telecommunications, Information, and Multimedia and Workshop

Conference

Conference1st International Conference on Forensic Applications and Techniques in Telecommunications, Information, and Multimedia and Workshop, e-Forensics 2008
Country/TerritoryAustralia
CityAdelaide
Period21/01/0823/01/08

Keywords

  • Machine grouping
  • Manufacturing cells
  • Particle swarm optimization

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