A Gene-Pool Based Genetic Algorithm for the Avoiding-Obstacle TSP

摘要：

Comparing with classical TSP (Traveling Salesman Problem), avoiding-obstacle TSP is harder, more practical, but insufficiently studied. In this paper, this problem is modeled as a path optimization with constraints, and then solved by a non-constraint Genetic Algorithm based a gene-pool, where stores all best feasible routes of adjacent points, aiming to apply the traditional non-constraint techniques by calculating the local routes in advance. Experiments shows that up to 100 points TSPs with different kinds of random obstacles are tacked in reasonable time based on above methods.

关键词： Gene-Pool Avoiding-Obstacle TSP Genetic Algorithm

作者: Jing Chen Zhenhua Li Dan Zhao

作者单位: School of Computer Science, China University of Geosciences, Lumo Road 388, Wuhan 430074, China. School of Computer Science, China University of Geosciences, Lumo Road 388, Wuhan 430074, China.

会议类型: 国际会议

会议名称: The Second International Symposium on Intelligence Computation and Applications(ISICA 2007)(第二届智能计算及其应用国际会议)

会议地点: 武汉

会议语种:英文

在线出版日期: 2007-09-21（万方平台首次上网日期，不代表论文的发表时间）