摘要
Traveling salesman problem (TSP) is a classical NP-hard problem in combinational optimization. This paper adopted a novel genetic algorithm which adjust the crossover probability and mutation probability adaptively based on clustering and fuzzy system, and designed a new crossover operator to improve the performance of genetic algorithm (GA) for TSP. Experiments show that the proposed method is much better than the standard genetic algorithm with a higher convergent rate and success rate.
- 出版日期2008
- 单位中山大学