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Genetics-based machine learning approach to production scheduling-a case of in-tree type precedence relation

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3 Author(s)
H. Tamaki ; Dept. of Electr. & Electron. Eng., Kobe Univ., Japan ; M. Ochi ; M. Araki

This paper introduces a method of generating and selecting rules for adjusting the priorities of jobs by using genetics-based machine learning (GBML) techniques. In applying the GBML, the authors use the Pitts approach, where the set of rules (rule-set) are represented symbolically as an individual of genetic algorithms, and the fitness of an individual is calculated based on the makespan of the schedule generated by using the rule-set. They actually carried out computational experiments for several problems, which indicate that the method of applying the GBML is effective for finding good rule-sets

Published in:

Industrial Electronics, 1998. Proceedings. ISIE '98. IEEE International Symposium on  (Volume:2 )

Date of Conference:

7-10 Jul 1998