CROSSOVER OPERATORS IN GENETIC ALGORITHMS: A REVIEW

The performance of Genetic Algorithm (GA) depends on various operators. Crossover operator is one of them. Crossover operators are mainly classified as application dependent crossover operators and application independent crossover operators. Effect of crossover operators in GA is application as wel...

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Bibliographic Details
Published in:ICTACT journal on soft computing 2015-10, Vol.6 (1), p.1083-1092
Main Authors: A.J., Umbarkar, P.D., Sheth
Format: Article
Language:English
Subjects:
Crossover
Evolutionary Algorithm
Genetic Algorithm
Genetic Operators
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Summary:The performance of Genetic Algorithm (GA) depends on various operators. Crossover operator is one of them. Crossover operators are mainly classified as application dependent crossover operators and application independent crossover operators. Effect of crossover operators in GA is application as well as encoding dependent. This paper will help researchers in selecting appropriate crossover operator for better results. The paper contains description about classical standard crossover operators, binary crossover operators, and application dependant crossover operators. Each crossover operator has its own advantages and disadvantages under various circumstances. This paper reviews the crossover operators proposed and experimented by various researchers.
ISSN:0976-6561
2229-6956
DOI:10.21917/ijsc.2015.0150