多阶段传感器-武器-目标分配问题的建模与优化求解

Modeling and optimization of multi-stage sensor-weapon-target assignment

中文关键词  联合分配  传感器-武器-目标分配  构造型启发式算法  协同作战

英文关键词  Co-allocation  sensor-weapon-target assignment  constructive heuristic  cooperative engagement

中文摘要

      本文在静态传感器–武器–目标分配(S–WTA)问题的基础上, 将作战过程分为多个拦截阶段, 以最小化来袭 目标的剩余威胁的期望值为目标, 建立了一种多阶段S–WTA问题模型. 为了求解该问题, 本文将多阶段S–WTA问 题分解为两类作战资源分配子问题. 首先, 提出了一种基于知识的增量式构造型启发式算法对多阶段武器–目标分 配子问题进行求解. 根据已确定的多阶段武器–目标分配方案, 提出了一种基于边际损失的构造型启发式算法求解 多阶段传感器–目标分配子问题. 结合两种低复杂度、快速构造型启发式算法实现多阶段S–WTA问题的有效求解. 本文选取了基于随机排列(RP)的随机采样算法作为对比算法, 并通过仿真实验验证了算法的有效性. 实验结果表 明, 本文提出的算法在大部分算例的求解质量和时间成本上都优于RP算法.

英文摘要

      Based on the static variant of the sensor-weapon-target assignment (S–WTA) problem, we built a mathematical model for the multi-stage S–WTA problem, with the objective of minimizing the expected remaining threat value of the incoming targets, by dividing the operational process into several interception stages. In order to solve this problem, the multi-stage S–WTA problem was decomposed into two combat resource assignment subproblems. Firstly, a knowledge-based incremental constructive heuristic was proposed to solve the multi-stage weapon-target assignment subproblem. With the obtained weapon-target assignment scheme, a marginal-loss-based constructive heuristic was proposed to solve the multi-stage sensor-target assignment subproblem. Thus, we can obtain valid solutions of the multi-stage S– WTA problem by incorporating the proposed two fast constructive heuristic algorithms with low complexity. A random sampling method based on random permutations (RP) was employed as the competitor, and some simulation experiments were carried out to validate the effectiveness of the proposed heuristic. The computational result indicates that the proposed heuristic outperforms its competitor for most of the test instances, in terms of both solution quality and time cost.