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Alternative TitleImprovement of ant colony algorithm based on cloud models theory
段海滨; 王道波; 于秀芬; 朱家强; 北京8701信箱
Source Publication哈尔滨工业大学学报
Keyword云模型理论 蚁群算法 信息素 定性关联规则
Other AbstractAnt 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.
Funding Project中国科学院空间科学与应用研究中心
Document Type期刊论文
Corresponding Author北京8701信箱
Recommended Citation
GB/T 7714
段海滨,王道波,于秀芬,等. 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.
APA 段海滨,王道波,于秀芬,朱家强,&北京8701信箱.(2005).基于云模型理论的蚁群算法改进研究.哈尔滨工业大学学报,37(1),115-119.
MLA 段海滨,et al."基于云模型理论的蚁群算法改进研究".哈尔滨工业大学学报 37.1(2005):115-119.
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