Abstract: Aiming at the defects such as long search time and tending to be trapped by local optimization for ant colony algorithm on solving Traveling Agent Problem（TAP）, this paper proposes an improves algorithm which integrates ant and bee colony algorithm. The algorithm is more suitable for the characteristics of TAP by modifying the state transition probability and pheromone updating rules. This algorithm makes the ants search for the optimal solution as soon as possible by introducing the thought of follow bees. The algorithm adding the obstruction factor avoids the shortcoming that the solution is trapped easily in the local optimum. The simulation results show that the algorithm for resolving the TAP avoids effectively the above-mentioned disadvantages of the ant colony algorithm, and also show that the algorithm is superior to other related methods on the performance of solution.

Key words: traveling Agent problem, ant colony algorithm, bee colony algorithm, follow ants, obstruction factor

摘要： 针对蚁群算法在解决旅行Agent问题（TAP）时存在搜索时间长和易陷入局部最优的缺点，提出一种将蜂群和蚁群算法相结合的新型算法。通过修改状态转移概率和信息素更新规则使算法更符合TAP问题的特征，引入跟随蜂思想使蚂蚁尽快搜索到问题最优解，加入阻塞度因子以避免算法陷入局部最优。仿真结果表明，该算法在解决旅行Agent问题时有效避免了蚁群算法的上述缺点，且在解的性能上优于相关算法。

关键词: 旅行Agent问题, 蚁群算法, 蜂群算法, 跟随蚁, 阻塞度因子