| 基于云模型的参数自适应蚁群遗传算法 |
| |
| 引用本文： | 牟峰,王慈光,袁晓辉,薛锋.基于云模型的参数自适应蚁群遗传算法[J].系统工程与电子技术,2009,31(7):1763-1766. |
| |
| 作者姓名： | 牟峰 王慈光 袁晓辉 薛锋 |
| |
| 作者单位： | 1. 西南交通大学交通运输学院, 四川, 成都, 610031;2. 西南交通大学信息科学与技术学院, 四川, 成都, 610031 |
| |
| 摘 要： | 蚁群算法基于正反馈机制进行全局搜索,具有很强的全局收敛能力;遗传算法具有极强的快速全局搜索能力。为了充分发挥两种算法在寻优过程中的优势,提出一种基于正态云关联规则的自适应参数调节蚁群遗传算法。该算法利用云关联规则实现了蚁群策略和遗传策略的有效融合,极大程度地发挥其整体功能,动态地平衡了算法收敛速度和搜索范围之间的矛盾,最后通过实例证明了其在解决TSP问题时的有效性。
|
| 关 键 词： | 蚁群算法 遗传算法 蚁群遗传算法 正态云模型 旅行商问题 |
| 收稿时间： | 2008-05-05 |
| 修稿时间： | 2008-09-03 |
ACGA with adapting parameters based on cloud models |
| |
| MU Feng,WANG Ci-guang,YUAN Xiao-hui,XUE Feng.ACGA with adapting parameters based on cloud models[J].System Engineering and Electronics,2009,31(7):1763-1766. |
| |
| Authors: | MU Feng WANG Ci-guang YUAN Xiao-hui XUE Feng |
| |
| Institution: | 1. Coll. of Traffic and Transportation, Southwest Jiaotong Univ., Chengdu 610031, China;2. School of Information Science & Technology, Southwest Jiaotong Univ., Chengdu 610031, China |
| |
| Abstract: | The ant colony algorithm(ACA) has a good global convergence capability by using the mechanism of positive feedback,while genetic algorithm(GA) has a capacity for performing global searches and being quick.CACGA(ant colony-genetic algorithm with adapting parameters based on cloud models) is proposed to take advantage of good qualities of the two optimization algorithms more completely.CBACGA makes the ant colony strategy and the genetic strategy to be fused ingeniously through the cloud association rule,which can utilize the whole function of the algorithm effectively and can dynamically appease the contradiction between the convergent speed and the searching scope.The simulation result for TSP shows its validity. |
| |
| Keywords: | |
| 本文献已被 万方数据 等数据库收录！ |
| 点击此处可从《系统工程与电子技术》浏览原始摘要信息 |
| 点击此处可从《系统工程与电子技术》下载免费的PDF全文 |
|
