A multi-objective PSO for job-shop scheduling problems

Most previous research into the job-shop scheduling problem has concentrated on finding a single optimal solution (e.g., makespan), even though the actual requirement of most production systems requires multi-objective optimization. The aim of this paper is to construct a particle swarm optimization...

Full description

Saved in:
Bibliographic Details
Published in:Expert systems with applications 2010-03, Vol.37 (2), p.1065-1070
Main Authors: Sha, D.Y., Lin, Hsing-Hung
Format: Article
Language:English
Subjects:
Job-shop scheduling
Multiple objectives
Particle swarm optimization
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Most previous research into the job-shop scheduling problem has concentrated on finding a single optimal solution (e.g., makespan), even though the actual requirement of most production systems requires multi-objective optimization. The aim of this paper is to construct a particle swarm optimization (PSO) for an elaborate multi-objective job-shop scheduling problem. The original PSO was used to solve continuous optimization problems. Due to the discrete solution spaces of scheduling optimization problems, the authors modified the particle position representation, particle movement, and particle velocity in this study. The modified PSO was used to solve various benchmark problems. Test results demonstrated that the modified PSO performed better in search quality and efficiency than traditional evolutionary heuristics.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2009.06.041