| 进化蚁群优化理论实现障碍距离分析 |
| |
| 引用本文： | 谭新莲,武凤翔,陆彦辉.进化蚁群优化理论实现障碍距离分析[J].计算机工程与应用,2009,45(22):224-227. |
| |
| 作者姓名： | 谭新莲 武凤翔 陆彦辉 |
| |
| 作者单位： | 1.郑州大学 信息工程学院，郑州 450001 2.华北水利水电学院 水利职业学院，郑州 450002 |
| |
| 摘 要： | 借鉴了机器人路径规划问题的解决思路，将遗传算法中交叉算子引入到蚁群优化算法的路径寻优过程，提出了一种基于进化蚁群优化算法的障碍距离分析算法。实验结果表明，该方法不仅能处理复杂形状的障碍，与基于遗传算法的障碍距离计算方法相比，具有较好的路径寻优能力，并且能够很好地降低搜索陷入局部最优的可能性。
|
| 关 键 词： | 空间分析 障碍距离 蚁群优化算法 遗传算法 |
| 收稿时间： | 2009-1-9 |
| 修稿时间： | 2009-3-23
|
Obstacles distance analysis based on evolution ant colony optimization |
| |
| TAN Xin-lian,WU Feng-xiang,LU Yan-hui.Obstacles distance analysis based on evolution ant colony optimization[J].Computer Engineering and Applications,2009,45(22):224-227. |
| |
| Authors: | TAN Xin-lian WU Feng-xiang LU Yan-hui |
| |
| Affiliation: | 1.School of Information Engineering，Zhengzhou University，Zhengzhou 450001，China 2.Water Conservancy Vocational School，North China Institute of Water Conservancy and Hydroelectric Power，Zhengzhou 450002，China |
| |
| Abstract: | On the basis of the paper used in robot path planning problem solving ideas,and the crossover operation of genetic algorithm is used in the ant colony system for path optimization.This paper proposes a novel analyse algorithm of obstacle distance using ant colony optimization.Experimental results show that the proposed algorithm is capable of handling any complex shape obstacles and has better path planning optimization ability than genetic algorithm,and it can reduce the probability of local optimum. |
| |
| Keywords: | spatial analysis obstacles distance ant colony optimization genetic algorithm |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《计算机工程与应用》浏览原始摘要信息 |
|
点击此处可从《计算机工程与应用》下载全文 |
