分布式任务计划动态调整模型及算法

战时任务计划的动态调整是当前作战指挥领域研究的热点问题。首先描述了分布式兵力组织的组成要素,对规划问题进行了建模,并且提出了平台定价模型。然后设计了一个分布式的协作框架,用来实现任务计划的动态调整,该框架由两个模块构成,第一部分是内部模块,该模块包括一个N-best算法和一个反馈策略,完成决策实体内部的二次分配;第二部分是外部模块,当任务精度低于期望值时调用此模块,实现决策实体间的协作。最后通过仿真实验证明了该模型的有效性,并讨论了模型在不同情况下的适用性。

Distributed dynamic task plan adjustment model and algorithm

The dynamic adjustment of the task plan during the war is a hotspot problem in battle command field. Firstly, the elements of the distributed military organization are described, and a platform pricing model is put forward to solve the planning problem. Secondly, a distributed coordination framework is designed to realize the dynamic adjustment of the task plan. This coordination framework consists of two parts. One is an intra-module which includes a N-best algorithm and a tradeoff strategy to achieve the secondary allocation in the inner of the decision maker, and the other is an extra module which can achieve the collaboration between decision makers when the task accuracy is less than the desired accuracy. Finally, simulation experiment results show the effectiveness of the proposed model, and the applicability of this model in different conditions is also discussed.