DocumentCode
3211696
Title
Orthogonal particle swarm optimization for multi-objective job shop scheduling problems
Author
Feng, Mingyue ; Tang, Shaoxun ; Li, Hua ; Li, Wei ; Guo, Can ; Xu, Youchun ; Zhang, Yongjin
Author_Institution
Dept. of Automotive Eng., Mil. Transp. Inst., Tianjin, China
Volume
1
fYear
2010
fDate
13-14 Sept. 2010
Firstpage
256
Lastpage
260
Abstract
The multi-objective job shop scheduling problem is a popular topic in manufactural management domain in recent years. This paper presents a multi-objective orthogonal particle swarm optimization (MOOPSO) for this problem. MOOPSO introduces the orthogonal design method from the field of experiment design to prevent the algorithm from being premature and falling into local optima, which in turns improves the global solution space exploring capability. Feasibility and efficiency of MOOPSO are verified through numerical experiments by comparing it with some other algorithms.
Keywords
job shop scheduling; particle swarm optimisation; global solution space exploring capability; local optima; manufactural management; multiobjective job shop scheduling; orthogonal particle swarm optimization; Optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Natural Computing Proceedings (CINC), 2010 Second International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-7705-0
Type
conf
DOI
10.1109/CINC.2010.5643846
Filename
5643846
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