摘要
目前,蚁群算法已被广泛应用于解决大量的组合优化问题,但基本蚁群算法搜索时间较长,容易陷入局部最优解的缺点比较突出。该文在基本蚁群算法模型的基础上,将贪心算法融入其动态转移过程中,提出一种基于贪心策略的动态自适应改进方法,并将改进后的算法应用于TSP问题。最后通过对比仿真,证明改进算法的可行性和有效性。
Currently,ant colony algorithm has been widely used to solve large combination optimization problems,but the prominent shortcoming of the basic ant colony algorithm is easily trapped into local optimal solution.In this paper,the author propose an improved algorithm that it is based on greedy strategy,and applied to TSP.It is proved that the improved algorithm is feasible and effective in the emulation experiments.
出处
《计算机与数字工程》
2012年第1期37-39,共3页
Computer & Digital Engineering
关键词
贪心策略
蚁群算法
自适应
greedy strategy
ant colony algorithm
self-adaption
