摘要
蚁群算法作为近年来一种新的模拟进化算法具有较强的发现解的能力,但同时也有收敛慢、耗费时间的缺点.本文针对各种不同规模的TSP问题,通过实验对各参数的设置做了研究,并对蚂蚁初始化提出了新的算法,并进行了实验验证.
As a novel simulated evolutionary algorithm which was proposed in recent years, ant colony optimization （ACO） algorithm has great capability in searching better solutions,but ACO also has the shortcoming of slow converging. For different dimensions of TSP problems, the paper studies the settings of parameters with experiments, and proposes a new method of the initialization of ants system. Experimental results indicate that the enhancement is practical.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2006年第8期1530-1533,共4页
Acta Electronica Sinica
关键词
蚁群算法
蚂蚁系统的初始化
参数设置
旅行商问题
ant algorithm
the initialization of ants system
optimum configurations
Traveling Salesman Problem （TSP）
