Improved Ant Colony Algorithm for Traveling Salesman Problems
An improved ant colony algorithm is proposed in this paper for Traveling Salesman Problems (TSPs). In the process of searching, the ants are more sensitive to the optimal path because the inverse of distance among cities is chosen as the heuristic information, while a candidate list is used to limit the number of candidate city. The method of local and global dynamic phenomenon update is used in order to adjust the distribution of phenomenon according to the routes. The method of 2-opt is only used for the current optimal tour, enhancing the convergence speed. The simulation results demonstrate the proposed algorithm works well and efficient.
Ant colony algorithm Path planning Dynamic pheromone updating TSPs
Pei-dong Wang Gong-You Tang Yang Li Xi-Xin Yang
College of Information Science and Engineering, Ocean University of China, Qingdao, 266100
国际会议
The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)
太原
英文
660-664
2012-05-23（万方平台首次上网日期，不代表论文的发表时间）