A PARTICLE SWARM OPTIMIZATION ALGORITHM ON JOB-SHOP SCHEDULING PROBLEMS WITH MULTI-PURPOSE MACHINES

Pisut Pongchairerks () and Voratas Kachitvichyanukul ()
Additional contact information
Pisut Pongchairerks: Industrial Engineering Program, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani, 12121, Thailand
Voratas Kachitvichyanukul: Industrial Engineering and Management, School of Engineering and Technology, Asian Institute of Technology, Pathum Thani, 12120, Thailand

Asia-Pacific Journal of Operational Research (APJOR), 2009, vol. 26, issue 02, 161-184

Abstract: 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-PSOcis a metaheuristic that can be applied to many types of optimization problems, where MPMJSP is one of these types. To apply GLN-PSOcin MPMJSP, a procedure to map the position of particle into the solution of MPMJSP is proposed. Throughout this paper, GLN-PSOccombined 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.

Keywords: Particle swarm optimization; job-shop scheduling; MPMJSP; makespan (search for similar items in EconPapers)
Date: 2009
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0217595909002158
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:apjorx:v:26:y:2009:i:02:n:s0217595909002158

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0217595909002158

Access Statistics for this article

Asia-Pacific Journal of Operational Research (APJOR) is currently edited by Gongyun Zhao

More articles in Asia-Pacific Journal of Operational Research (APJOR) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().