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基于改进层次聚类法的指挥控制资源部署
引用本文:周翔翔,姚佩阳,王欣. 基于改进层次聚类法的指挥控制资源部署[J]. 系统工程与电子技术, 2012, 34(3): 523-528. DOI: 10.3969/j.issn.1001-506X.2012.03.17
作者姓名:周翔翔  姚佩阳  王欣
作者单位:空军工程大学电讯工程学院, 陕西 西安 710077
基金项目:国家高技术研究发展计划(863计划)(2010AAJ146);空军工程大学研究生科技创新专项计划(Dx2010307)资助课题
摘    要:以网络化作战战场资源部署为研究背景,对战术指挥控制资源部署问题进行了描述。以决策实体工作负载的均方根最小为目标函数,建立了指挥控制资源部署问题的数学模型,提出了基于改进层次聚类法的指挥控制资源部署算法。该算法以作战任务-平台资源的分配结果为输入信息,对可部署决策实体数目范围设定、决策实体合并项选择和决策实体能力约束判定进行了改进,着重分析了每一层聚类的N-best备选策略和决策实体合并项选择方法。通过一个作战想定,分别从目标函数值、搜索空间大小两个方面对本算法和其他算法进行了比较。

关 键 词:指挥控制资源  决策实体  层次聚类  N-best备选策略

Command and control resource deployment based on improved hierarchical clustering method
ZHOU Xiang-xiang,YAO Pei-yang,WANG Xin. Command and control resource deployment based on improved hierarchical clustering method[J]. System Engineering and Electronics, 2012, 34(3): 523-528. DOI: 10.3969/j.issn.1001-506X.2012.03.17
Authors:ZHOU Xiang-xiang  YAO Pei-yang  WANG Xin
Affiliation:Telecommunication Engineering Institute, Air Force Engineering University, Xi’an 710077, China
Abstract:Based on the research background of networked operation battlefield resource deployment,the tactical command and control resource deployment problem is described.The minimum of the root mean-square of the decision-making entities’ workloads is taken as the objective function,a mathematical model is set up.Then,an algorithm based on the improved hierarchical clustering is presented.With the input information of task-platform assignment results,the hierarchical clustering method is improved with three aspects: the setting of the number range of decision-making entities,the selection method of combination items from current decision-making entities,and the assessment of the decision-making entities’ capability restrictions.In each layer clustering,the N-best standby strategy and the combination item selection method are analyzed detailedly.Based on an operational scenario,the performances of the proposed algorithm are compared with other algorithms.
Keywords:command and control resource  decision-making entity  hierarchical clustering  N-best standby strategy
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