Research Article

Analysis of Selection Schemes for Solving an Optimization Problem in Genetic Algorithm

by  Poonam Sharma, Amit Wadhwa, Komal
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 93 - Issue 11
Published: May 2014
Authors: Poonam Sharma, Amit Wadhwa, Komal
10.5120/16256-5714
PDF

Poonam Sharma, Amit Wadhwa, Komal . Analysis of Selection Schemes for Solving an Optimization Problem in Genetic Algorithm. International Journal of Computer Applications. 93, 11 (May 2014), 1-3. DOI=10.5120/16256-5714 

                        @article{ 10.5120/16256-5714,
                        author  = { Poonam Sharma,Amit Wadhwa,Komal },
                        title   = { Analysis of Selection Schemes for Solving an Optimization Problem in Genetic Algorithm },
                        journal = { International Journal of Computer Applications },
                        year    = { 2014 },
                        volume  = { 93 },
                        number  = { 11 },
                        pages   = { 1-3 },
                        doi     = { 10.5120/16256-5714 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2014
                        %A Poonam Sharma
                        %A Amit Wadhwa
                        %A Komal
                        %T Analysis of Selection Schemes for Solving an Optimization Problem in Genetic Algorithm%T 
                        %J International Journal of Computer Applications
                        %V 93
                        %N 11
                        %P 1-3
                        %R 10.5120/16256-5714
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

Genetic algorithm is a population based an adaptive search and optimizations techniques and genetic mimic the natural evolution process. The Genetic operators include selection, crossover and mutation. The aim to present this paper is it gives comparative selection strategies for solving an optimization problem in genetic algorithm and evaluates their performance.

References
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Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Selection Crossover Roulette Wheel Selection Rank Selection Tournament Selection Elitism Selection.

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