A feature model of genetic algorithm for generalized traveling salesman problem

作者：Wu, Guangchao; Huang, Han^*

来源：Journal of Information and Computational Science, 2009, 6(1): 155-161.

• Combinational optimization
• Comparative studies
• Crossover operator
• Feature analysis
• Feature modeling
• Generalized traveling salesman problem
• Hybrid chromosome genetic algorithms

Generalized Traveling Salesman Problem (GTSP) is one of the challenging combinational optimization problems in a number of applications. A hybrid chromosome genetic algorithm (HCGA) was proposed as an improvement of generalized chromosome genetic algorithm (GCGA) which was considered as the best algorithm for GTSP. In this paper, a comparative study of HCGA and GCGA is carried on. A feature model for GA's encoding is built as a theoretical tool. Based on the feature analysis, HCGA's crossover operator can be proved to be more powerful in searching. Later, HCGA can be verified to get better solution than GCGA, which was also shown by the testing results. Therefore, the reason why HCGA performs better than GCGA in solving GTSP is explained theoretically.

• 出版日期2009-1
• 单位华南理工大学