DocumentCode
424181
Title
Genetic algorithm application on the job shop scheduling problem
Author
Wu, C.G. ; Xing, X.L. ; Lee, H.P. ; Zhou, C.G. ; Liang, Y.C.
Author_Institution
Coll. of Comput. Sci. & Technol., Jilin Univ., Changchun, China
Volume
4
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
2102
Abstract
Based on the concepts of operation template and virtual job shop, this paper attempts to solve several job shop scheduling problems with different scale and analyzes the relationship among the population size, mutation probability, the number of evolving generations and the complexity of the undertaking problem visually by using the trend chart of the fitness curves. This visual analysis could provide some referencing information for the adjustment of genetic algorithm running parameters.
Keywords
genetic algorithms; job shop scheduling; travelling salesman problems; fitness curves; genetic algorithm; job shop scheduling problem; traveling salesman problem; visual analysis; Algorithm design and analysis; Application software; Computer science; Genetic algorithms; Genetic mutations; High performance computing; Information analysis; Job shop scheduling; Performance analysis; Processor scheduling;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1382144
Filename
1382144
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