针对巡飞弹群协同执行侦察、打击和评估的任务分配问题,考虑任务时序约束、目标属性异构特征以及支持多弹共同执行一个任务的需求,提出一种基于联合投标的一致性包拍卖算法(Joint-bidding-based Consensus Based Bundle Algorithm,JCBBA),以实现异构任务分配。在构建弹群协同“察打评”任务分配问题的组合优化模型的基础上,基于CBBA架构,定制任务包构建机制、个体竞标策略和考虑联合投标的边际收益计算方法,实现无中心通信条件下时序任务协同分配的快速鲁棒求解。多场景仿真试验结果表明,JCBBA可以在满足多种约束的前提下实现时序约束任务的合理分配,性能对比试验结果表明JCBBA能够更好地权衡协同任务分配的求解时效性和结果最优性,求解耗时相比一致性联盟算法减少约40%。
Abstract
For the task assignment of loitering munition swarm cooperatively conducting the reconnaissance,attack and assessment (RAA) tasks,a joint-bidding-based consensus-based bundle algorithm (JCBBA) is proposed by taking into account the constraint of time precedence,the heterogeneous characteristics of target property and the requirement of supporting the multiple munitions to jointly execute an identical task.Munition swarm task assignment of cooperative RAA is first formulated as combinatorial optimization problems.Then based on the structure of CBBA,a task bundle construction mechanism,an individual biding strategy and a marginal benefits computation method considering joint biding are tailored to achieve the fast and robust assignment of task with time precedence constraint in non-center communication networks.Numerical simulations under different scenarios show that JCBBA can achieve reasonable allocation of time precedence tasks while multiple constraints are satisfied,and the comparison tests demonstrate that JCBBA could better trade-off the computation efficiency and optimality with the solving time reduced by approximately 40% compared to consensus-based coalition algorithm.