DocumentCode
3425215
Title
Solving the traveling salesman problem through genetic algorithms with changing crossover operators
Author
Takahashi, Ryouei
Author_Institution
Hachinohe Inst. of Technol., Hachinohe Aomori, Japan
fYear
2005
fDate
15-17 Dec. 2005
Abstract
In order to solve the traveling salesman problem (TSP) through genetic algorithms (GAs), a method of changing crossover operators (CXO), which can flexibly substitute the current crossover operator for another suitable crossover operator at any time, is proposed. This paper reports experimental validation of CXO through C software by using data of 200 cities.
Keywords
genetic algorithms; travelling salesman problems; C software; changing crossover operator; genetic algorithm; traveling salesman problem; Biological cells; Cities and towns; Flowcharts; Genetic algorithms; Machine learning; Traveling salesman problems;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Applications, 2005. Proceedings. Fourth International Conference on
Print_ISBN
0-7695-2495-8
Type
conf
DOI
10.1109/ICMLA.2005.58
Filename
1607469
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