Improved Ant Colony Optimization and Application on TSP
Ant Colony Optimization is an intelligent optimization algorithm from the observations of ant colonies foraging behavior.However,ACO usually cost more searching time and get into early stagnation during convergence Process.We design the improved ant colony algorithm using perturbation method to avoid early stagnation,adjusting volatilization coefficient to increase the exploration of tours at first phase and searching speed at second phase,using hortation method to improved searching efficiency.We apply the improved algorithm on traveling salesman problem showing that the improved algorithm finds the best values more quickly and more stability than Max-Min Ant System algorithm.
Ant Colony Optimization TSP Pheromone Perturbation Method
Zhiqiang Fu Leian Liu
The Academy of Computer Science and Engineering Zhongkai University of Agricultural and Engineer,Guangzhou 510225,China
国际会议
沈阳
英文
2055-2058
2012-09-07（万方平台首次上网日期，不代表论文的发表时间）