DocumentCode
2233384
Title
Learning based dynamic approach to job-shop scheduling
Author
Wei, Liang ; Haibin, Yu
Author_Institution
Shenyang Inst. of Autom., Chinese Acad. of Sci., Shenyang, China
Volume
3
fYear
2001
fDate
2001
Firstpage
274
Abstract
Dynamic selection of scheduling rules during real operations has been recognized as a promising approach to the scheduling of the production. This paper studies the dynamic job-shop scheduling and presents a fuzzy logic based learning approach. Experiment results show that the presented method outperforms the basic rules which are proved to perform well for such problem and that the proposed approach computes quickly enough to meet the requirements of dynamic scheduling
Keywords
computer aided production planning; fuzzy logic; learning (artificial intelligence); probability; production control; real-time systems; dynamic scheduling; fuzzy logic; induced learning; job-shop scheduling; probability distribution; production control; real time system; scheduling rules; Artificial intelligence; Dispatching; Dynamic scheduling; Fuzzy logic; Job shop scheduling; Probability distribution; Processor scheduling; Production; Single machine scheduling; Vehicle dynamics;
fLanguage
English
Publisher
ieee
Conference_Titel
Info-tech and Info-net, 2001. Proceedings. ICII 2001 - Beijing. 2001 International Conferences on
Conference_Location
Beijing
Print_ISBN
0-7803-7010-4
Type
conf
DOI
10.1109/ICII.2001.983069
Filename
983069
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