DocumentCode
2041233
Title
Using ants as a genetic crossover operator in GLS to solve STSP
Author
Ismkhan, Hassan ; Zamanifar, Kamran
Author_Institution
Comput. Dept., Univ. of Isfahan, Isfahan, Iran
fYear
2010
fDate
7-10 Dec. 2010
Firstpage
344
Lastpage
348
Abstract
Ant Colony Algorithm (ACA) and Genetic Local Search (GLS) are two optimization algorithms that have been successfully applied to the Traveling Salesman Problem (TSP). In this paper we define new crossover operator then redefine ACA´s ants as operate according to defined crossover operator then put forward our GLS that uses these ants to solve Symmetric TSP (STSP) instances.
Keywords
genetic algorithms; search problems; travelling salesman problems; ACA; GLS; STSP; TSP; ant colony algorithm; genetic crossover operator; genetic local search; optimization algorithms; symmetric TSP; traveling salesman problem; Arrays; Cities and towns; Classification algorithms; Conferences; Genetics; Search problems; Traveling salesman problems; ACA; GLS; Heuristic crossover; Local search;
fLanguage
English
Publisher
ieee
Conference_Titel
Soft Computing and Pattern Recognition (SoCPaR), 2010 International Conference of
Conference_Location
Paris
Print_ISBN
978-1-4244-7897-2
Type
conf
DOI
10.1109/SOCPAR.2010.5686165
Filename
5686165
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