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:	Lim, Siew Mooi, Md. Sultan, Abu Bakar, Sulaiman, Md. Nasir, Mustapha, Aida, Leong, Kuan Yew
Format:	Article
Language:	English
Published:	IACSIT Press 2017
Online Access:	http://psasir.upm.edu.my/id/eprint/53868/ http://psasir.upm.edu.my/id/eprint/53868/1/Crossover%20and%20mutation%20operators%20of%20genetic%20algorithms.pdf

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