| Article ID: | iaor20052367 |
| Country: | China |
| Volume: | 13 |
| Issue: | 1 |
| Start Page Number: | 17 |
| End Page Number: | 22 |
| Publication Date: | Feb 2004 |
| Journal: | Operations Research and Management Science |
| Authors: | Shu Jinlong, Zhao Zhe, Dai Qiaoyan |
| Keywords: | genetic algorithms |
In this paper, we design new operators of Genetic Algorithms (GA) to solve multi-group TSPs by searching the population of feasible solutions, exchanging information between genomes and keeping the relatively efficient genetic information. We give the principle and methods to solve multi-group TSP. A computer simulated experiment shows that the calculation complexity of GA is small and the solutions that are close to optimal can be found easily by GA.