DocumentCode :
3275716
Title :
Genetic algorithm based scheduling in a dynamic manufacturing environment
Author :
Bierwirth, Christian ; Kopfer, Herbert ; Mattfeld, Dirk C. ; Rixen, Ivo
Volume :
1
fYear :
1995
fDate :
Nov. 29 1995-Dec. 1 1995
Firstpage :
439
Abstract :
The application of adaptive optimization methods to production scheduling has recently become a research topic of broad interest. Genetic algorithm approaches to scheduling concentrate on static problems, whereas real world scheduling tends to be dynamic. The paper briefly outlines the application of a genetic algorithm to the dynamic job shop problem. In a second step the job shop is regarded as a non deterministic optimization problem arising from the occurrence of job releases. A temporal decomposition of the non deterministic problem leads to a scheduling control that combines simulation and adaptive search
Keywords :
Automatic control; Dispatching; Dynamic scheduling; Environmental economics; Genetic algorithms; Job shop scheduling; Manufacturing systems; Optimization methods; Production; Programmable control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 1995., IEEE International Conference on
Conference_Location :
Perth, WA, Australia
Print_ISBN :
0-7803-2759-4
Type :
conf
DOI :
10.1109/ICEC.1995.489188
Filename :
489188
Link To Document :
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