中文摘要：

为了克服单身者的缺省，寻找趋势，在殖民地的蚂蚁被划分成几亚群。在不同亚群的蚂蚁有不同小道信息和期望系数。模仿的退火的方法被介绍给算法。通过使温度随着重复变化，在旅游的每拐弯以后，当候选人设定，蚂蚁获得的答案集合被拿。更改集合被在候选人集合把答案加到以前的更改集合，概率由温度决定了获得。在候选人集合的答案被用来更新小道信息。在更新的每拐弯，当前的最好的答案也被用来在当前的最好的线路上提高小道信息。当算法处于停滞状态时，小道信息被重设。计算机实验证明建议算法有更高的稳定性和集中速度。

英文摘要：

To overcome the default of single search tendency, the ants in the colony are divided into several sub-groups. The ants in different subgroups have different trail information and expectation coefficients. The simulated annealing method is introduced to the algorithm. Through setting the temperature changing with the iterations, after each turn of tours, the solution set obtained by the ants is taken as the candidate set. The update set is obtained by adding the solutions in the candidate set to the previous update set with the probability determined by the temperature. The solutions in the candidate set are used to update the trail information. In each turn of updating, the current best solution is also used to enhance the trail information on the current best route. The trail information is reset when the algorithm is in stagnation state. The computer experiments demonstrate that the proposed algorithm has higher stability and convergence speed.