基于RHP-IVFSA的多智能体编组#br#任务分配动态优化

智能体编组协同作战中任务分配的动态优化问题,提出一种基于滚动时域策略的多编组任务分配动态优化方法。以任务执行效率为目标函数,建立了满足个体任务时窗和编组资源损耗约束的问题模型。给出与突发事件特征对应的预测窗口、滚动窗口和滚动驱动机制。设计了一种改进快速模拟退火对优化子问题予以求解,给出解方案表达、邻域解生成、冲突消解等步骤,采用高温随机贪婪搜索、回火技术、禁忌设计和精英保留策略,避免算法陷入局部最优,提高算法的计算效率。案例的仿真计算表明,所建模型和求解方法可以对多编组任务分配计划进行在线优化,并使任务的执行效率始终维持较高水平。

Dynamic task allocation in multiple agent groups based on RHP IVFSA

The aim of this study is to provide a solution based on rolling horizon to dynamical optimization of aerial multiple grouping task allocation. According to the time window attribute of partial tasks and resource capability wastage character of groups, the mathematical model with the value of task executed efficiency maximization objective is built, which satisfy with former constraints. The strategy elements are given, including the prediction time window, rolling time window and driven mechanism. An improved very fast simulated annealing algorithm is developed to solve the sub optimized problem. Solution coding, neighborhoods creating and conflict solving methods are proposed, then the random greedy search measure at high temperature, re annealing mechanism, tabu policy and elitist reserved policy are applied, so that the IVFSA can improve computing efficiency and avoid local optimum solutions. At last, the superiority and applicability of this approach are illuminated by the simulation of assumption, which ensure the stability of task executed efficiency at high level.