系统工程与电子技术

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反导预警作战资源调度方法

赵新爽1,2, 汪厚祥2, 蔡益朝1   

  1. 1. 空军预警学院空天预警实验室, 湖北 武汉 430019;
    2. 海军工程大学电子工程学院, 湖北 武汉 430033
  • 出版日期:2015-05-25 发布日期:2010-01-03

Resource scheduling method in antimissile early warning campaign

ZHAO Xin-shuang1,2, WANG Hou-xiang1, CAI Yi-chao2   

  1. 1. Space and Air Early Warning Lab, Air Force Early Warning Academy, Wuhan 430019, China;
    2. Electronic Engineering College, Naval University of Engineering, Wuhan 430033, China
  • Online:2015-05-25 Published:2010-01-03

摘要:

针对反导预警作战中多部预警资源协同探测多批弹道导弹目标的问题,根据反导预警作战资源调度的特点,提出了反导预警作战任务分解策略,并以调度效益、交接次数和资源负载均衡度为目标建立了多目标优化模型。通过重新设计粒子编码方式以及对重新定义粒子群优化算法中的位置更新公式,使其适用于求解离散变量优化问题。针对粒子群优化算法容易过早收敛的缺点,在进行局部搜索时使用变邻域搜索算法,从而增强算法的寻优能力。通过仿真实验验证,将两种算法相结合能够快速有效地解决反导预警作战资源调度问题。

Abstract:

In order to solve the problem that several equipment detect multi-target in antimissile early warning campaign, the task decomposition strategy based on the endpoint is proposed, which is according to the characteristics of resource scheduling for antimissile early warning. A multi-objective optimization model is established based on this task decomposition strategy, and the objective of this model includes scheduling benefit, handover times and resource loading degree. By redesigning the particle encoding mode and redefinition the position updating formula in particle swarm optimization, the algorithm is suitable for solving the discrete optimization problem. Aiming at the problem of premature, a modified algorithm combining the particle swarm optimization-variable neighborhood search is presented. The experimental results show that this algorithm can resolve the problem of resource scheduling for antimissile early warning rapidly and effectively, and it has good application value.