分工合作的加权蚁群算法*

针对蚁群算法搜索时间长、易于陷入局部最优解的缺点，提出一种新的改进算法——分工合作的加权蚁群算法。此算法采取分工合作的方式，在信息素初始化、状态转移概率中分别加入权值，并运用遗传算法中排序的概念对信息素更新机制进行排序加权，此外对信息素上限加以限制。最后以TSP为例，验证了此改进算法不但在收敛速度上有了大幅度提高，而且有效避免了易于陷入局部最优解的缺点，从而证明了提出的新算法是合理有效的。

Ant colony algorithm with division-cooperation of labor and weight

For ant colony algorithm had a long searching time and was easy to fall in local optimal, this paper proposed a new kind of improvement algorithm: ant colony algorithm with division-cooperation of labor and weight. This new algorithm adopted a mode of division-cooperation of labor, and added weights in the initialization of pheromone and the rate of state transfer respectively. At the same time, it made sort-weight to the update of pheromone with the concept of sort in the genetic algorithm. Furthermore, limited the maximal pheromone. At last, used TSP to testify the validity of the new algorithm. The result proves the improved algorithm enhances the convergence largely and effectively avoid getting into local optimal easily.