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.
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.
出处
《软件学报》
EI
CSCD
北大核心
2002年第12期2317-2323,共7页
Journal of Software
基金
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
