低轨预警系统动态任务规划启发式算法

Heuristic Algorithm for Dynamic Task Planning of Early Warning System of Low Earth Orbit

该文针对低轨预警系统任务动态规划需求,从预警传感器资源和导弹跟踪任务角度对低轨预警系统动态任务规划问题进行了形式化描述,建立了系统动态任务规划的动态约束满足问题模型。该模型包括两级优化目标——跟踪精度、资源利用率、传感器切换率、松弛度综合优化指标和方案调整幅度(调整率)指标;提出了求解动态规划问题的变邻域启发式搜索算法,设计了算法的直接插入、重新分配、替换和删除邻域结构及算子。通过仿真实验验证了基于梯度优化目标的动态规划模型的合理性,并说明启发式算法能有效求解低轨预警系统动态任务规划问题。

The dynamic task planning issue of early warning system of Low Earth Orbit （LEO） is described by the system resource and missile tracking task aspects, and the Dynamic Constraint Satisfaction Problem （DCSP） model of system dynamic task planning is built which includes two level index the integrative optimizing indexes of tracking precision, task accomplishment, sensor switching and resource slack, the adjusting range of original task planning scheme. To solve the dynamic planning model, a variable neighborhood heuristic algorithm on the basis of original planning and schedule is put forward, and the directly insert, redistribute, replace and delete neighborhood structure and their operators are designed in the heuristic algorithm. The simulation results show the leveled dynamic planning model is rational and the heuristic algorithm can solve the dynamic task planning issue of early warning system of LEO effectively.