DocumentCode :
3083154
Title :
Learning-aided dynamic scheduling and its application to routing problem
Author :
Nakasuka, Shinichi ; Yoshida, Taketoshi
Author_Institution :
IBM Res., Tokyo Res. Labs., Japan
fYear :
1990
fDate :
5-7 Dec 1990
Firstpage :
1612
Abstract :
Learning-aided dynamic scheduling is proposed for production line scheduling. In this concept, the scheduling rules are dynamically switched during real operations to reflect changes in the production line status, given requirements and constraints. This switching is governed by some knowledge which is automatically acquired by machine learning during the iteration of simulations of the specific production line. The machine learning is carried out in the form of generation of a binary decision tree, and an algorithm is developed for this objective. Simulation studies on its application to a routing problem have been performed, and the effectiveness of the concept was verified
Keywords :
knowledge engineering; learning systems; production control; scheduling; trees (mathematics); binary decision tree; knowledge engineering; learning-aided dynamic scheduling; production line scheduling; routing problem; simulation iteration; Dynamic scheduling; Flexible manufacturing systems; Humans; Job shop scheduling; Machine learning; Machine learning algorithms; Processor scheduling; Production systems; Real time systems; Routing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 1990., Proceedings of the 29th IEEE Conference on
Conference_Location :
Honolulu, HI
Type :
conf
DOI :
10.1109/CDC.1990.203886
Filename :
203886
Link To Document :
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