DocumentCode
505039
Title
Job shop scheduling using Estimation of Distribution Algorithms
Author
Fujimoto, Masahiro ; Eguchi, Toru
Author_Institution
Grad. Sch. of Eng., Hiroshima Univ., Hiroshima, Japan
fYear
2009
fDate
18-21 Aug. 2009
Firstpage
2627
Lastpage
2630
Abstract
This paper presents an application of estimation of distributed algorithms to the job shop scheduling with the objective to minimize tardiness of jobs. The priority values for job selection are coded as genes and estimated by EDAs. Three kinds of methods for estimating the priorities are tested. In addition, the optimization method using the mixture of EDA and an effective priority rule for job selection is examined. Numerical experiments show that the performance of EDAs is comparable to that of a genetic algorithm using a random key coding.
Keywords
genetic algorithms; job shop scheduling; random codes; EDA; distributed algorithms; distribution algorithm estimation; genetic algorithm; job selection; job shop scheduling; job tardiness; priority rule; random key coding; Biological cells; Decoding; Distributed algorithms; Electronic design automation and methodology; Genetic algorithms; Job shop scheduling; Optimization methods; Routing; Scheduling algorithm; Testing; Estimation of Distribution Algorithm; Genetic Algorithm; Job Shop Scheduling; Priority Rule;
fLanguage
English
Publisher
ieee
Conference_Titel
ICCAS-SICE, 2009
Conference_Location
Fukuoka
Print_ISBN
978-4-907764-34-0
Electronic_ISBN
978-4-907764-33-3
Type
conf
Filename
5335171
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