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
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;
Conference_Titel :
Machine Learning and Applications, 2005. Proceedings. Fourth International Conference on
Print_ISBN :
0-7695-2495-8
DOI :
10.1109/ICMLA.2005.58
