面向舰艇编队的无人机集群物资补给规划研究  

Research on unmanned aerial vehicles supply planningfor warship formations

作　　者：郭文强[1] 李子展 候勇严 薛博丰 GUO Wen-qiang;LI Zi-zhan;HOU Yong-yan;XUE Bo-feng(School of Electronic Information and Artificial Intelligence,Shaanxi University of Science&Technology,Xi′an 710021,China;School of Electrical and Control Engineering,Shaanxi University of Science&Technology,Xi′an 710021,China)

机构地区：[1]陕西科技大学电子信息与人工智能学院,陕西西安710021 [2]陕西科技大学电气与控制工程学院,陕西西安710021

出　　处：《陕西科技大学学报》2023年第5期169-173,188,共6页Journal of Shaanxi University of Science & Technology

基　　金：陕西省科技厅重点研发计划项目(2020SF-286);陕西省西安市科技计划项目(23GXFW0004);陕西科技大学博士科研启动基金项目(2023BJ-01)。

摘　　要：面向多约束条件下的舰艇编队物资补给规划任务,本文综合考虑无人机集群在执行补给任务时的作业以及惩罚时间成本,设计了规划模型的优化目标函数,并以舰艇补给时间窗、无人机最大载重量等为约束条件,构建了物资补给规划模型.为了解决自适应遗传算法(AGA)易陷入局部最优的问题,设计了非线性概率函数用于确定交叉概率和变异概率,并提出了一种基于非线性自适应遗传算法的无人机物资补给规划方法(NLAGA).实验结果表明:在标准算例Solomen求解问题上NLAGA方法优于AGA和改进的AGA方法;在最优的补给时间成本条件下,NLAGA方法能有效地实现舰艇编队的物资补给任务中无人机集群数量确定和飞行路径规划.For the material supply planning of warship formation under constraint conditions,this paper designs the optimization objective function of the planning model,based on the operation and penalty time cost of unmanned aerial vehicles(UAVs),ship supply time window,maximum load capacity of UAV and other constraints.In order to solve the problem that adaptive genetic algorithm(AGA)is prone to fall into local optimum,a nonlinear probability function is designed to determine the crossover probability and mutation probability.Furthermore,a UAV material supply planning based on nonlinear adaptive genetic algorithm(NLAGA)is proposed.The experimental results show that the NLAGA method is superior to AGA and the improved AGA method in solving the Solomen problem of the standard calculation example.Under the condition of optimal supply time and cost,NLAGA method can effectively determine the number of UAVs and flight path planning in the material supply task of the warship formation.

关 键 词：补给规划模型 遗传算法 非线性概率函数 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]