摘要
多无人机协同侦察与攻击是现代信息化战争的一种重要军事行动方式,对多无人机协同来说,任务规划技术至关重要,也是一个复杂的决策与优化问题。考虑多无人机的任务执行能力、能源资源和所受威胁等约束,采用多旅行商问题建立了多无人机协同任务规划问题的组合优化模型,并采用改进的遗传算法对模型进行修正求解。仿真结果验证了该算法的有效性。
Collaborative reconnaissance and attack of multiple unmanned aerial vehicles(UAVs)is an important way of military operation in modern information war.For multi-UAV cooperation,the mission planning is crucial,and also is a complicated decision-making and optimization problem.Considering the constraints of task executive capability,energy resources and suffered threats,etc.,this paper establishes the combinatorial optimization model of collaborative task planning for multi-UAVs by means of multi-travelling salesman problem(MTSP),and uses the modified genetic algorithm to perform the correction and solution for the model.Simulation results verify the effectiveness of the algorithm.
作者
赵民全
ZHAO Min-quan(Unit 92785 of PLA,Huludao 125208,China)
出处
《舰船电子对抗》
2020年第4期44-47,共4页
Shipboard Electronic Countermeasure
关键词
多旅行商问题
遗传算法
模拟退火算法
协同决策与控制
任务规划
multi-travelling salesman problem
genetic algorithm
simulated annealing algorithm
cooperative decision and control
task planning
