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Crossover Operators in Genetic Algorithms:A Review


Affiliations
1 Department of Information Technology, Walchand College of Engineering, India
2 Department of Master of Computer Applications, Government College of Engineering, Karad, India
     

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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.

Keywords

Evolutionary Algorithm, Genetic Algorithm, Crossover, Genetic Operators.
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  • Crossover Operators in Genetic Algorithms:A Review

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Authors

A. J. Umbarkar
Department of Information Technology, Walchand College of Engineering, India
P. D. Sheth
Department of Master of Computer Applications, Government College of Engineering, Karad, India

Abstract


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.

Keywords


Evolutionary Algorithm, Genetic Algorithm, Crossover, Genetic Operators.

References