基于改进鱼群算法的多无人机任务分配研究  

Research on Multi-UAV Cooperative Task Allocation Based on Improved Fish Swarm Algorithm

作　　者：杨尚君[1] 孙永维[1] 庞宇[1] 

机构地区：[1]中国人民解放军95988部队

出　　处：《计算机仿真》2015年第1期69-72,102,共5页Computer Simulation

摘　　要：多无人机协同任务分配问题是多无人机协同控制的关键,为解决单目标函数构建的任务分配模型不能满足决策者对战场环境大量信息的需求,以最大航程和最长任务执行时间作为多无人机任务分配的两个目标函数,依据多目标优化理论,建立了协同任务分配多目标优化模型。并采用了一种借鉴遗传算法中的变异思想的改进鱼群算法进行求解,得到多无人机任务分配的多目标最优解集,然后根据决策者的偏好选择最佳任务分配方案。最后将上述算法应用于多无人机协同任务分配中并进行了仿真,仿真结果验证了改进鱼群算法的收敛性及有效性,为多无人机协同任务分配优化提供了参考依据。Multi-UAV cooperative task allocation problem is the key to multi-UAV cooperative control. In order to solve the task allocation model which is based on single objective function and can not provide large battlefield environment information for the decision-makers, based on multi-objective optimization theory, a multi-objective optimization model of cooperative task allocation was established, and the maximum voyage and maximum task execution time were treated as two optimization objective functions. On this basis, an improved fish swarm algorithm with the variation idea of the genetic algorithm was adopted for obtaining the multi-objective optimization solution set of multi -UAV task allocation, then the decision makers can select the best task allocation scheme according to their prefer- enee. Finally, the algorithm was applied to the simulation of multi-UAV cooperative task allocation, the simulation results demonstrate the convergence and effectiveness of the improved fish swarm algorithm.

关 键 词：无人作战机 任务分配 多目标优化 鱼群算法 

分 类 号：V279[航空宇航科学与技术—飞行器设计] V24