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Article:A Comparative Study of Adaptive Crossover Operators for Genetic Algorithms to Resolve the Traveling Salesman Problem

by ABDOUN Otman, ABOUCHABAKA Jaafar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 31 - Number 11
Year of Publication: 2011
Authors: ABDOUN Otman, ABOUCHABAKA Jaafar
10.5120/3945-5587

ABDOUN Otman, ABOUCHABAKA Jaafar . Article:A Comparative Study of Adaptive Crossover Operators for Genetic Algorithms to Resolve the Traveling Salesman Problem. International Journal of Computer Applications. 31, 11 ( October 2011), 49-57. DOI=10.5120/3945-5587

@article{ 10.5120/3945-5587,
author = { ABDOUN Otman, ABOUCHABAKA Jaafar },
title = { Article:A Comparative Study of Adaptive Crossover Operators for Genetic Algorithms to Resolve the Traveling Salesman Problem },
journal = { International Journal of Computer Applications },
issue_date = { October 2011 },
volume = { 31 },
number = { 11 },
month = { October },
year = { 2011 },
issn = { 0975-8887 },
pages = { 49-57 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume31/number11/3945-5587/ },
doi = { 10.5120/3945-5587 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:17:57.155393+05:30
%A ABDOUN Otman
%A ABOUCHABAKA Jaafar
%T Article:A Comparative Study of Adaptive Crossover Operators for Genetic Algorithms to Resolve the Traveling Salesman Problem
%J International Journal of Computer Applications
%@ 0975-8887
%V 31
%N 11
%P 49-57
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Genetic algorithm includes some parameters that should be adjusting so that the algorithm can provide positive results. Crossover operators play very important role by constructing competitive Genetic Algorithms (GAs). In this paper, the basic conceptual features and specific characteristics of various crossover operators in the context of the Traveling Salesman Problem (TSP) are discussed. The results of experimental comparison of more than six different crossover operators for the TSP are presented. The experiment results show that OX operator enables to achieve a better solutions than other operators tested.

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Index Terms

Computer Science
Information Sciences

Keywords

Travelers Salesman Problem Genetic Algorithm NP-Hard Problem Crossover Operator probability of crossover Genetic Algorithm

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