Abstract：To overcome the default of local optimal solution in the traditional ant colony algorithm, a modified ant colony optimization (AFACO) was proposed based on attractive field. The principle of attraction field based on pheromone was analyzed in detail to establish the attractive field model. The attractive field factor based on pheromone was designed, and the pheromone updating strategy was provided to improve the collaboration among ants nearby. For the standard 30 city traveling salesman problem, the optimization results from the proposed algorithm were compared with those from basic ant colony algorithm and some other improved ant colony. The results show that the optimal solution of TSP problem is 423.74, while the optimal and the mean solution of Oliver30 are 423.74 and 423.96, respectively, which shows the improved ant colony algorithm has good ability for searching the global optimal solution.
王雷, 李明, 刘志虎. 基于吸引场的蚁群算法在TSP中的应用[J]. 江苏大学学报（自然科学版）, 2015, 36(5): 573-577.
Wang Lei, Li Ming, Liu Zhihu. Application of an ant colony optimization based on attractive field in TSP[J]. Journal of Jiangsu University(Natural Science Eidtion)
, 2015, 36(5): 573-577.
2015, Vol. 36 
