Ant Colony Optimization Algorithm Based on Immune Strategy
Ant Colony Optimization (ACO) is inspired by the ability of ant colonies to find shortest paths between their nest and a food source. The paper proposed a modified ACO based on artificial immune strategy. The mechanism of the vaccination, antibody diversity and clonal deletion theory in artificial immune system are introduced to improve the ways of artificial ants search solution space and the elite ants capability. Also it can solve the conflict between the diversity of the solutions searched by ant colony and the convergence speed. The simulation results by examples of traveling salesman problem (TSP) show that adding immune strategy to ants group can find better solution in shorter time than ACO.
ant colony optimization artificial immune traveling salesman problem antibody vaccination
Xiaoxia Zheng Yang Fu
Shanghai University of Electric Power Shanghai ,China,200090
国际会议
杭州
英文
655-658
2011-10-28（万方平台首次上网日期，不代表论文的发表时间）