Solving the traveling salesman problem through genetic algorithms with changing crossover operators

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.