蚁群算法(ant colony algorithm，简称ACA)是20世纪90年代由意大利学者M．Dorigo等人首先提出来的一种新型的模拟进化算法．它的出现为解决NP一难问题提供了一条新的途径．用蚁群算法求解旅行商问题(TSP)、分配问题(QAP)、调度问题(JSP)等，取得了一系列较好的实验结果．虽然对蚁群算法研究的时间不长，但是初步研究已显示出蚁群算法在求解复杂优化问题(特别是离散优化问题)方面具有一定的优势，表明它是一种很有发展前景的方法．蚁群算法的主要特点是：正反馈、分布式计算．正反馈过程使它能较快地发现问题的较好解；分布式易于并行实现，将它与启发式算法相结合，易于发现较好解．-ACO (ant colony algorithm, referred to as ACA) is the 1990s by the Italian scholar M. Dorigo, who first proposed a new type of simulated evolutionary algorithm. It appears to solve NP-hard problem provides a new way. Ant colony algorithm for traveling salesman problem (TSP), distribution (QAP), scheduling problems (JSP), etc., made ​ ​ a series of good results. Although the ant colony algorithm is not long, but preliminary studies have shown that the ant colony algorithm in solving complex optimization problems (in particular, discrete optimization problem) has certain advantages, that it is a promising approach. The main features of ant colony algorithm is: positive feedback, distributed computing. Positive feedback process so that it can quickly find a better solution of the problem　distributed easy-to-parallel implementation, it would be combined with the heuristic algorithm, easy to find better solutions.