蚁群算法求解连续空间优化问题的一种方法

陈崚; 沈洁; 秦玲

引用本文:	陈崚,沈洁,秦玲.蚁群算法求解连续空间优化问题的一种方法.软件学报,2002,13(12):2317-2323

【打印本页】【下载PDF全文】【查看/发表评论】【EndNote】【RefMan】【BibTex】

←前一篇|后一篇→

过刊浏览高级检索

本文已被：浏览 4785次下载 9828次	码上扫一扫！
分享到：微信更多字体:加大+\|默认\|缩小-
蚁群算法求解连续空间优化问题的一种方法
陈崚^1,2, 沈洁¹, 秦玲¹
1.扬州大学计算机科学与工程系,江苏,扬州,225009;2.南京大学计算机软件新技术国家重点实验室,江苏,南京,210093

摘要:

针对蚁群算法不太适合求解连续性优化问题的缺陷,提出用蚁群算法求解连续空间优化问题的一种方法.该方法将解空间划分成若干子域,在蚁群算法的每一次迭代中,首先根据信息量求出解所在的子域,然后在该子域内已有的解中确定解的具体值.以非线性规划问题为例所进行的计算结果表明,该方法比使用模拟退火算法、遗传算法具有更好的收敛速度.

关键词: 蚁群算法优化遗传操作非线性规划问题

DOI：

分类号:

基金项目:国家自然科学基金资助项目(60074013);国家高性能计算基金资助项目(00219);江苏省教育厅自然科学基金项目(99KJB520003);南京大学计算机软件新技术国家重点实验室开放基金资助项目

A Method for Solving Optimization Problem in Continuous Space by Using Ant Colony Algorithm

CHEN Ling,SHEN Jie,QIN Ling

Abstract:

A drawback of ant colony algorithm is not suitable for solving continuous optimization problems. A method for solving optimization problem in continuous space by using ant colony algorithm is presented. By dividing the space into subdomains, in each iteration of the ant colony algorithm, the method first find the subdomain in which the solution located by using the trail information, then the values of the components in the solution can be determined from the existing solutions in the subdomain. The experimental results on the nonlinear programming problem show that the method has much higher convergence speed than that of GA and SA.

Key words: ant colony algorithm optimization genetic operation non-linear programming problem