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| 基于云模型理论的蚁群算法改进研究 | |
| 引用本文： | 段海滨,王道波,于秀芬,朱家强.基于云模型理论的蚁群算法改进研究[J].哈尔滨工业大学学报,2005,37(1):115-119. |
| 作者姓名： | 段海滨 王道波 于秀芬 朱家强 |
| 作者单位： | 1. 南京航空航天大学,自动化学院,江苏,南京,210016 2. 中国科学院,空间科学与应用研究中心,北京,100080 3. 清华大学,智能技术与系统国家重点实验室,北京,100084 |
| 基金项目： | 航空基础科学基金资助项目(01C52015) 江苏省“333工程”基金资助项目． |
| 摘 要： | 近几年优化领域中新出现的蚁群算法采用分布式并行计算机制，易于与其它方法结合，具有较强的鲁棒性。但易限于局部最优解是其最突出的缺点．云模型是一种新的实现定性概念和定量数值之间转换的有力工具，本文在介绍云模型理论的基础上，提出了一种利用云模型来有效限制蚁群算法陷入局部最优解的方法，最后将基于云模型理论的改进蚁群算法与未改进的蚁群算法分别应用于著名的CHC144 TSP进行实验．改进后的蚁群算法采用升半正态云规则进行控制，并选取了500个云滴，仿真计算结果证明了该方法的有效性和可行性． |
| 关 键 词： | 云模型理论 蚁群算法 信息素 定性关联规则 |
| 文章编号： | 0367-6234(2005)01-0115-05 |
| 修稿时间： | 2004年3月3日 |
Improvement of ant colony algorithm based on cloud models theory |
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| DUAN Hai-bin,WANG Dao-bo,YU Xiu-fen,ZHU Jia-qiang.Improvement of ant colony algorithm based on cloud models theory[J].Journal of Harbin Institute of Technology,2005,37(1):115-119. | |
| Authors: | DUAN Hai-bin WANG Dao-bo YU Xiu-fen ZHU Jia-qiang |
| Abstract: | Ant colony algorithm is a new category of parallelized bionic algorithm in optimization fields. It has strong robustness and is easy to combine with other methods in optimization, but it is easy to fall in local best. Cloud models theory is a powerful tool to convert numerical quantitative analysis to conceptual qualitative analysis. On the basis of introduction of cloud models, a novel qualitative strategy for improving the global optimization properties by use of cloud models is proposed. Finally, the computational experiments on CHC144 TSP have been performed. In the experiments, the rule of increasing half normal cloud is adopted in the improved ant colony algorithm, and the optimal number of cloud drops is 500. Simulation results show that this novel method has certain validity and feasibility. |
| Keywords: | cloud models theory ant colony algorithm pheromone qualitative association rule |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |
