2011Journal of Jiangsu Radio & Television UniversityRequires access

Research and Application of Improved Crossover in Genetic Algorithm

TV Universit

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Abstract

Crossover operator is one of the important genetic operators,which is the processing of getting two different new individuals by operating parental individuals.It has important influence on the searching results of genetic algorithm.Crossover operator can deliver good genes to the next generation.Improved crossover operator proposed in this paper,which is improved from crossover probability and strategy,can be applied to function optimization.Comparing to the typical genetic algorithm,it has more optimum performance,and can get better solutions.

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What this paper is about

Crossover operator is one of the important genetic operators,which is the processing of getting two different new individuals by operating parental individuals.It has important influence on the searching results of genetic algorithm.Crossover operator can deliver good genes to the next generation.Improved crossover operator proposed in this paper,which is improved from crossover probability and strategy,can be applied to function optimization.Comparing to the typical genetic algorithm,it has more optimum performance,and can get better solutions.

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Available abstract

Crossover operator is one of the important genetic operators,which is the processing of getting two different new individuals by operating parental individuals.It has important influence on the searching results of genetic algorithm.Crossover operator can deliver good genes to the next generation.Improved crossover operator proposed in this paper,which is improved from crossover probability and strategy,can be applied to function optimization.Comparing to the typical genetic algorithm,it has more optimum performance,and can get better solutions.

Key concepts: Crossover, Genetic algorithm, Operator (biology), Computer science, Algorithm, Genetic operator, Mathematical optimization, Function (biology)

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