Crossover and mutation operators of genetic algorithms

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Crossover and mutation operators of genetic algorithms

Genetic algorithms (GA) are stimulated by population genetics and evolution at the population level where crossover and mutation comes from random variables. The problems of slow and premature convergence to suboptimal solution remain an existing struggle that GA is facing. Due to lower diversity in...

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Bibliographic Details
Main Authors:	Siew, Mooi Lim, Md. Sultan, Abu Bakar, Sulaiman, Md. Nasir, Mustapha, Aida, Leong, K. Y.
Format:	Article
Language:	English
Published:	International Association of Computer Science and Information Technology 2017
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://eprints.uthm.edu.my/3688/ http://eprints.uthm.edu.my/3688/1/AJ%202017%20%28515%29.pdf

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