| 用改进蚁群算法求解多目标优化问题 |
| |
| 引用本文： | 唐泳,马永开.用改进蚁群算法求解多目标优化问题[J].电子科技大学学报(社会科学版),2005(2). |
| |
| 作者姓名： | 唐泳 马永开 |
| |
| 作者单位： | 电子科技大学管理学院 成都610054
(唐泳)，电子科技大学管理学院 成都610054(马永开) |
| |
| 摘 要： | 蚁群算法是一种崭新的仿生模拟进化算法,该算法在许多领域已经得到应用。多目标优化问题是一类很重要的优化问题,优化与求解较难。对此,提出了一种改进蚁群算法用于求解多目标优化问题,得到一组变量的权重后,用一定数量的蚂蚁在解空间中首先随机搜索,然后模拟蚂蚁寻食的方式,通过信息素来指引搜索。给出了具体的算法,示例仿真说明了其有效性,并表明该算法可以快速发现多个全局最优解。
|
| 关 键 词： | 多目标优化 蚁群算法 模拟进化算法 仿生算法 |
An Improved Ant Colony Algorithm for Multi-Objective Optimization |
| |
| TANG Yong,MA Yong-kai.An Improved Ant Colony Algorithm for Multi-Objective Optimization[J].Journal of University of Electronic Science and Technology of China(Social Sciences Edition),2005(2). |
| |
| Authors: | TANG Yong MA Yong-kai |
| |
| Abstract: | Ant Colony Algorithm is a brand-new bionic simulated evolutionary algorithm, which has been applied to many fields. Multi-objective optimization problems are very important optimization problems. Its hard to optimized or solved. An improved Ant Colony Algorithm to solve Multi-objective optimization problems is introduced. After setting up a set of weight for the parameters, the algorithm uses some ants search in the solution space first in a stochastic way then stimulate the food searching behavior of real ants to guide the search by the pheromone. The new algorithm is explained in details and some simulations show the algorithm is very effective in finding global optimizations. |
| |
| Keywords: | Multi-objective optimization Ant colony algorithm simulated evolutionary algorithm bionic algorithm |
| 本文献已被 CNKI 等数据库收录！ |
|
