摘要
蚁群算法是一种新型的模拟仿生算法。本文通过在一般函数优化求解中的应用,说明该算法与启发式因子相结合可有效地避开陷入局部最优的弊病。显示了蚁群算法在连续空间优化问题中的应用前景。
Ant Colony algorithm is a novel simulated evolutionary algorithm. In this paper , Ant algorithm applied to function optimization can effectively overcome the commonly seen disadvantage of getting into local optimum, and can show the good performance of the algorithm in the function optimization.
出处
《太原科技大学学报》
2005年第3期210-212,共3页
Journal of Taiyuan University of Science and Technology
基金
山西省自然科学基金资助项目(20021046)
关键词
蚁群算法
函数优化
连续函数
ant colony algorithm, function optimization, continuous function.
