A Hybrid Model for Solving TSP Based on Artificial Immune and Ant Colony
Artificial immune algorithm has rapid and random overall search ability, but cannot utilize system feedback information sufficiently, which results in redundancy and iteration as well as low solving efficiency. Ant colony algorithm has distributed parallel overall search ability, and can be converged on optimal path by the accumulation and update of information pheromone, but there is a lack of early stage pheromone, and the solving speed is low. This thesis put forth a hybrid algorithm based on artificial immune algorithm and ant colony algorithm, which applies artificial immune algorithm to generate pheromone distribution, and ant colony algorithm for optimal solving. When this algorithm is applied to make computer simulation to solve TSP, it turned out that this algorithm is an optimal method with preferable converging speed and search ability.
artificial immune ant colony algorithm TSP
Wang Dian gang Peng Xiao qiang Guo Hong Ying Ze gui
Communication and Automation Center of Sichuan Electric Power Company Chengdu, China Sichuan Electric Vocational and Technical College Chengdu, China
国际会议
太原
英文
605-609
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）