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A Novel and Efficient Selection Method in Genetic Algorithm

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2015
Authors:
Smit Anand, Nishat Afreen, Shama Yazdani
10.5120/ijca2015907067

Smit Anand, Nishat Afreen and Shama Yazdani. Article: A Novel and Efficient Selection Method in Genetic Algorithm. International Journal of Computer Applications 129(15):7-12, November 2015. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Smit Anand and Nishat Afreen and Shama Yazdani},
	title = {Article: A Novel and Efficient Selection Method in Genetic Algorithm},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {129},
	number = {15},
	pages = {7-12},
	month = {November},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

The performance of a Genetic Algorithm (GA) is inspired by a number of factors: the choice of the selection method the type of crossover operator, the rate of mutation, population size etc. GA allows a diverse population to evolve under a specific selection scheme to fitter population. Therefore, the choice of the selection method plays a very important role in the maximization of the fitness function of the evolved population. In this paper, a novel selection method called “Alternis” has been proposed. This study emphasizes on the comparison among the different selection methods used in GAs and the proposed method and evaluate their performance. Results of this study highlight the significant differences among the various selection schemes. The influence of the various selection methods on the performance of genetic algorithm can be estimated to assist the preference of a selection method. The aim of this paper is to propose a selection method which gives best overall performance in a widely diverse population.

References

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Keywords

Genetic algorithm, Chromosomes, Crossover, Mutation, Fitness function.