AntColony

  蚁群算法是一种模仿蚁群行为的仿生优化算法，其实现机理包括两个基本阶段：适应阶段和协作阶段。在适应阶段，各可行解根据积累的信息不断调整自身结构，路径上经过的蚂蚁越多，信息量越大，则该路径越容易被选择：时间越长，信息量越小。在协作阶段，各可行解之间通过信息交流，以期望产生性能更好的解。(Ant colony algorithm is a mimic ant colony behavior of bionic optimization algorithm, its implementation mechanism includes two basic stages: adaptation and collaboration. In adaptive phase, the feasible solution according to the accumulated information constantly adjust their structure, path through the more the ants, the greater the amount of information, it is the easier path is chosen: the longer the time, the smaller the amount of information. The collaboration stage, through the exchange of information between the feasible solution, expecting to generate better solutions.)