An empirical performance evaluation of a parameter-free genetic algorithm for job-shop scheduling problem

The Job-Shop Scheduling Problem (JSSP) is well known as one of the most difficult NP-hard combinatorial optimization problems. Several GA-based approaches have been reported for the JSSP. Among them, there is a parameter-free genetic algorithm (PfGA) for JSSP proposed by Matsui et al., based on an e...

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Veröffentlicht in:	2007 IEEE Congress on Evolutionary Computation S. 3796 - 3803
Hauptverfasser:	Matsui, S., Yamada, S.
Format:	Tagungsbericht
Sprache:	Englisch Japanisch
Veröffentlicht:	IEEE 01.09.2007
Schlagworte:	Algorithm design and analysis Biological cells Decoding Design engineering Genetic algorithms History Job shop scheduling Power engineering and energy Production Simulated annealing
ISBN:	1424413397, 9781424413393
ISSN:	1089-778X
Online-Zugang:	Volltext
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