摘要
传统的任务分配算法主要解决特定问题下的单目标优化问题,难以适应真实战场协同打击任务下复杂的态势。为此,考虑无人机协同打击任务中航迹长度、目标打击效果、目标价值收益、武器成本等因素构建无人机任务分配多目标优化模型,并基于非支配排序遗传算法(non-dominated sorting genetic algorithm,NSGA)-Ⅲ算法确定任务分配方案,对问题进行求解,从而得到帕累托最优解集。仿真结果表明本文提出的多目标任务分配模型及求解算法可为协同打击提供有效、可靠的多样化分配方案。
The traditional task assignment algorithm mainly solves the single target optimization under the specific problem,which is difficult to adapt to the complex situation under the real battlefield cooperative strike task.In view of the above problem,this paper constructs a multi-objective optimization model of UAV task assignment by considering the factors such as flight path length,target strike effect,target value and weapon cost in the cooperative strike mission of UAV to determine the task assignment scheme based on NSGA-Ⅲalgorithm,and the Pareto optimal solution set is obtained.The simulation results show that the multi-objective task assignment model and its solution proposed in this paper can provide an effective and reliable diversified assignment for cooperative strike.
作者
刘西
李贤
陈伟
从光涛
李如飞
LIU Xi;LI Xian;CHEN Wei;CONG Guangtao;LI Rufei(Shanghai Electro-Mechanical Engineering Institute,Shanghai 201109,China)
出处
《空天防御》
2021年第1期109-114,共6页
Air & Space Defense
