DocumentCode
3226995
Title
A genetic algorithm for job shop
Author
Falkenauer, E. ; Bouffouix, S.
Author_Institution
CRIF, Brussels, Belgium
fYear
1991
fDate
9-11 Apr 1991
Firstpage
824
Abstract
Genetic algorithms (GAs) constitute a technique that has been applied with advantage to a variety of combinatorial problems. This work shows how the GAs can be used to optimize the job shop problem with many tasks, many machines, and precedence constraints. The authors introduce the technique of GAs and then show what makes the treatment of the job shop scheduling difficult. They then present an encoding of the problem that overcomes these difficulties. The performance of the algorithm is demonstrated with examples of real-world size
Keywords
genetic algorithms; production control; genetic algorithms; job shop scheduling; precedence constraints; production control; Animals; Biological cells; Concurrent computing; Constraint optimization; Encoding; Genetic algorithms; Genetic mutations; Iterative algorithms; Job shop scheduling; Metals industry;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics and Automation, 1991. Proceedings., 1991 IEEE International Conference on
Conference_Location
Sacramento, CA
Print_ISBN
0-8186-2163-X
Type
conf
DOI
10.1109/ROBOT.1991.131689
Filename
131689
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