HYBRID ANT COLONY ALGORITHM BASED ON SCALE COMPRESSION

摘要：

To improve performance of ant colony algorithm when solving large-scale TSP problem, a hybrid ant colony algorithm based on scale compression is proposed.First we use genetic algorithm to generate a suboptimal solution set and calculate their intersection.By eliminating all cities mapped by the elements among the intersection in the primal TSP problem, we convert the original problem into a new one with smaller scale.In addition, we design a new optimal state transition rule based on regional characteristic of optimal solutions to accelerate convergence speed.Simulation results show our approach possess high searching ability and excellent convergence performance.

关键词： Ant Colony TSP Intersection Scale compression State transition rule

作者: JIAN-FENG YAN NA LI WEI-HUA LI HAO-BIN SHI

作者单位: School of Computer Science, Northwestern Polytechnical University, Shannxi 710072, China The 54th Research Institute of China Electronics Technology Group Corporation, HeBei 050081, China

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 885-889

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）