基于全局单位化的连续函数优化的改进蚁群算法  

An Improved Ant Colony Algorithm for Continuou Function Optimization Based on Global United

作　　者：周晓静[1] 吕翠英[1] 

机构地区：[1]华南理工大学数学科学学院,广东广州5106401

出　　处：《微电子学与计算机》2009年第4期54-57,共4页Microelectronics & Computer

摘　　要：提出了一种基于空间全局单位化的解决连续空间优化问题的改进蚁群算法.该算法首先通过单位映射将优化空间映射到单位空间,然后蚂蚁在各变量的每个位数上在0到9十个数字中进行选择,以此来模拟蚁群觅食的过程,并阐述了此改进蚁群算法的主要改进操作.通过实例测试表明,改进蚁群算法具有较好的寻优能力.This paper proposed an improved ant colony algorithm for continuous space optimization based on space global united. The improved ant colony algorithm firstly mapped the optimization space onto unit space by unit mapping, and then made the ant choose a figure in 0--9 on each numerical digit d each variable , simulating the process of the ants searching for fcxxt. Then the paper expounded the main improved operations of the improved ant colony algorithm. Finally made an optimization of test show that. the improved ant colony algorithm has better optimization ability.

关 键 词：蚁群算法 连续空间 优化 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]