关键词: 计算机应用, 蚁群算法, 旅行Agent问题, 信息素

Abstract: Ant colony algorithm is a novel category of bionic algorithm for optimization problems，which has the characteristic of parallelism，positive feedback and heuristic search，but it has the limitation of stagnation，and is easy to fall into local optimums.Traveling agent problem is a complex combinatorial optimization problem，which solves the problem of planning out an optimal migration path when agents migrate to several hosts.In this paper，an improved ant colony algorithm is presented.The local and global updating rules of pheromone are modified on the basis of ant colony algorithm，and a self-adaptive pheromone evaporation rate is proposed，which can accelerate the convergence rate and improve the ability of searching an optimum solution，so mobile agents can accomplish the migration task with high efficiency and short time.The results of contrastive experiments show that the algorithm is superior to other related methods both on the quality of solution and on the convergence rate.

Key words: computer application, ant colony algorithm, Traveling Agent Problem（TAP）, pheromone