English, Article edition: A PARTICLE SWARM OPTIMIZATION ALGORITHM ON JOB-SHOP SCHEDULING PROBLEMS WITH MULTI-PURPOSE MACHINES PISUT PONGCHAIRERKS; VORATAS KACHITVICHYANUKUL

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Bookmark: http://trove.nla.gov.au/version/40236
Physical Description
  • article
Language
  • English

Edition details

Title
  • A PARTICLE SWARM OPTIMIZATION ALGORITHM ON JOB-SHOP SCHEDULING PROBLEMS WITH MULTI-PURPOSE MACHINES
Author
  • PISUT PONGCHAIRERKS
  • VORATAS KACHITVICHYANUKUL
Physical Description
  • article
Notes
  • This paper is a contribution to the research which aims to provide an efficient optimization algorithm for job-shop scheduling problems with multi-purpose machines or MPMJSP. To meet its objective, this paper proposes a new variant of particle swarm optimization algorithm, called GLN-PSOc, which is an extension of the standard particle swarm optimization algorithm that uses multiple social learning topologies in its evolutionary process. GLN-PSOc is a metaheuristic that can be applied to many types of optimization problems, where MPMJSP is one of these types. To apply GLN-PSOc in MPMJSP, a procedure to map the position of particle into the solution of MPMJSP is proposed. Throughout this paper, GLN-PSOc combined with this procedure is named MPMJSP-PSO. The performance of MPMJSP-PSO is evaluated on well-known benchmark instances, and the numerical results show that MPMJSP-PSO performs well in terms of solution quality and that new best known solutions were found in some instances of the test problems.
  • Particle swarm optimization, job-shop scheduling, MPMJSP, makespan
  • RePEc:wsi:apjorx:v:26:y:2009:i:02:p:161-184
Language
  • English
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