摘要
为了提高时空域上对无人机协同侦察任务规划的效率,提出一种基于多种群合作演化遗传算法的任务规划模型。该模型建立了无人机协同侦察任务规划问题的分层描述,并将多种群合作演化遗传算法引入对模型的求解,设计了全局与局部搜索流程,交叉变异和合作演化等算法(子),并给出了详细求解步骤。仿真结果表明,所提模型及算法与单种群搜索算法相比,在任务处置效益、任务潜力效益、时间成本效益等方面均有提升。
In order to improve the efficiency of cooperative reconnaissance mission planning for UAVs in time-space,a task planning model based on multi-group cooperative evolutionary genetic algorithm is proposed.In this model,the hierarchical description of the task planning problem of UAV cooperative reconnaissance is established,and the multi-group cooperative evolution genetic algorithm is introduced to solve the model,the global and local search flow,cross-mutation and co-evolution algorithms(operator)and the other algorithms are designed,and the steps of solving the problem are given in detail.The simulation results show that the proposed model and algorithm can improve the efficiency of task disposal,task potential and time-cost compared with that of the single-population search algorithm.
作者
帅伟伟
汪君
任开君
杨健
林洁
SHUAI Weiwei;WANG Jun;REN Kaijun;YANG Jian;LIN Jie(Unit 95795 of PLA,Guilin 541003,China;No.15th Research Institute of China Electronics Technology Group Corporation,Beijing 100080,China)
出处
《火力与指挥控制》
CSCD
北大核心
2023年第4期173-177,183,共6页
Fire Control & Command Control
关键词
多种群
合作演化
无人机侦察
任务规划
multi-group
cooperative evolution
UAV reconnaissance
mission planning
