一、无人机模型简介:
单个无人机三维路径规划问题及其建模_IT猿手的博客-CSDN博客
参考文献:
[1]胡观凯,钟建华,李永正,黎万洪.基于IPSO-GA算法的无人机三维路径规划[J].现代电子技术,2023,46(07):115-120
二、高尔夫优化算法GOA简介
高尔夫优化算法(Golf Optimization Algorithm,GOA)由Montazeri Z等人于2023年提出,该算法模拟高尔夫运动过程中的球员击打高尔夫所采取的战术策略,能够有效平衡全局搜索和局部搜索的能力。
多目标优化算法:基于非支配排序的高尔夫优化算法(NSGOA)MATLAB-CSDN博客
[1] Montazeri Z, Niknam T, Aghaei J, Malik OP, Dehghani M, Dhiman G. Golf Optimization Algorithm: A New Game-Based Metaheuristic Algorithm and Its Application to Energy Commitment Problem Considering Resilience. Biomimetics. 2023; 8(5):386. Biomimetics | Free Full-Text | Golf Optimization Algorithm: A New Game-Based Metaheuristic Algorithm and Its Application to Energy Commitment Problem Considering Resilience
三、高尔夫优化算法GOA求解无人机路径规划
(1)部分代码
close all clear clc addpath('./Algorithm/')%添加算法路径 warning off; %% 三维路径规划模型定义 global startPos goalPos N N=2;%待优化点的个数(可以修改) startPos = [10, 10, 80]; %起点(可以修改) goalPos = [80, 90, 150]; %终点(可以修改) SearchAgents_no=30; % 种群大小(可以修改) Function_name='F1'; %F1:随机产生地图 F2:导入固定地图 Max_iteration=50; %最大迭代次数(可以修改) % Load details of the selected benchmark function [lb,ub,dim,fobj]=Get_Functions_details(Function_name); [Best_score,Best_pos,curve]=GOA(SearchAgents_no,Max_iteration,lb,ub,dim,fobj);%算法优化求解 AlgorithmName='GOA';%算法名字 figure semilogy(curve,'Color','r','linewidth',3) xlabel('迭代次数'); ylabel('飞行路径长度'); legend(AlgorithmName) display(['算法得到的最优适应度: ', num2str(Best_score)]); Position=[Best_pos(1:dim/3); Best_pos(1+dim/3:2*(dim/3)); Best_pos(1+(2*dim/3):end)]'; %优化点的XYZ坐标(每一行是一个点) plotFigure(Best_pos,AlgorithmName)%画最优路径
(2)部分结果
1.0000000e+01 1.0000000e+01 8.0000000e+01 1.1820429e+01 1.0571462e+01 8.1472989e+01 1.3550647e+01 1.1085750e+01 8.2868815e+01 1.5193235e+01 1.1545531e+01 8.4189899e+01 1.6750774e+01 1.1953473e+01 8.5438661e+01 1.8225847e+01 1.2312246e+01 8.6617520e+01 1.9621034e+01 1.2624518e+01 8.7728897e+01 2.0938916e+01 1.2892956e+01 8.8775212e+01 2.2182075e+01 1.3120229e+01 8.9758885e+01 2.3353092e+01 1.3309007e+01 9.0682335e+01 2.4454549e+01 1.3461955e+01 9.1547984e+01 2.5489026e+01 1.3581745e+01 9.2358249e+01 2.6459105e+01 1.3671043e+01 9.3115553e+01 2.7367367e+01 1.3732517e+01 9.3822314e+01 2.8216394e+01 1.3768838e+01 9.4480953e+01 2.9008766e+01 1.3782671e+01 9.5093889e+01 2.9747066e+01 1.3776687e+01 9.5663543e+01 3.0433874e+01 1.3753553e+01 9.6192335e+01 3.1071772e+01 1.3715938e+01 9.6682685e+01 3.1663341e+01 1.3666510e+01 9.7137012e+01 3.2211163e+01 1.3607937e+01 9.7557737e+01 3.2717817e+01 1.3542888e+01 9.7947279e+01 3.3185887e+01 1.3474031e+01 9.8308059e+01 3.3617953e+01 1.3404034e+01 9.8642497e+01 3.4016596e+01 1.3335567e+01 9.8953013e+01 3.4384399e+01 1.3271296e+01 9.9242026e+01 3.4723941e+01 1.3213891e+01 9.9511956e+01 3.5037805e+01 1.3166020e+01 9.9765225e+01 3.5328571e+01 1.3130350e+01 1.0000425e+02 3.5598821e+01 1.3109552e+01 1.0023145e+02 3.5851137e+01 1.3106292e+01 1.0044926e+02 3.6088099e+01 1.3123239e+01 1.0066007e+02 3.6312289e+01 1.3163062e+01 1.0086633e+02 3.6526288e+01 1.3228429e+01 1.0107044e+02 3.6732677e+01 1.3322008e+01 1.0127484e+02 3.6934038e+01 1.3446468e+01 1.0148193e+02 3.7132953e+01 1.3604477e+01 1.0169413e+02 3.7332001e+01 1.3798702e+01 1.0191388e+02 3.7533765e+01 1.4031814e+01 1.0214358e+02 3.7740826e+01 1.4306480e+01 1.0238566e+02 3.7955766e+01 1.4625368e+01 1.0264254e+02 3.8181164e+01 1.4991146e+01 1.0291663e+02 3.8419604e+01 1.5406484e+01 1.0321036e+02 3.8673666e+01 1.5874049e+01 1.0352615e+02 3.8945931e+01 1.6396509e+01 1.0386642e+02 3.9238981e+01 1.6976534e+01 1.0423358e+02 3.9555396e+01 1.7616791e+01 1.0463007e+02 3.9897759e+01 1.8319949e+01 1.0505829e+02 4.0268651e+01 1.9088676e+01 1.0552066e+02 4.0670652e+01 1.9925641e+01 1.0601962e+02 4.1106345e+01 2.0833511e+01 1.0655757e+02 4.1578310e+01 2.1814956e+01 1.0713694e+02 4.2089128e+01 2.2872643e+01 1.0776015e+02 4.2641382e+01 2.4009241e+01 1.0842961e+02 4.3237652e+01 2.5227418e+01 1.0914776e+02 4.3880520e+01 2.6529842e+01 1.0991700e+02 4.4572567e+01 2.7919183e+01 1.1073975e+02 4.5316374e+01 2.9398108e+01 1.1161845e+02 4.6114522e+01 3.0969285e+01 1.1255550e+02 4.6969593e+01 3.2635383e+01 1.1355333e+02 4.7884168e+01 3.4399071e+01 1.1461436e+02 4.8860829e+01 3.6263016e+01 1.1574100e+02 4.9902156e+01 3.8229887e+01 1.1693569e+02 5.1010732e+01 4.0302353e+01 1.1820083e+02 5.2189136e+01 4.2483081e+01 1.1953884e+02 5.3439952e+01 4.4774740e+01 1.2095216e+02 5.4765759e+01 4.7179999e+01 1.2244319e+02 5.6169139e+01 4.9701525e+01 1.2401436e+02 5.7652674e+01 5.2341987e+01 1.2566809e+02 5.9218944e+01 5.5104054e+01 1.2740679e+02 6.0870532e+01 5.7990393e+01 1.2923290e+02 6.2610017e+01 6.1003674e+01 1.3114882e+02 6.4439983e+01 6.4146564e+01 1.3315697e+02 6.6363009e+01 6.7421732e+01 1.3525979e+02 6.8381678e+01 7.0831846e+01 1.3745968e+02 7.0498570e+01 7.4379574e+01 1.3975907e+02 7.2716267e+01 7.8067586e+01 1.4216038e+02 7.5037350e+01 8.1898548e+01 1.4466602e+02 7.7464401e+01 8.5875130e+01 1.4727842e+02 8.0000000e+01 9.0000000e+01 1.5000000e+02
四、完整MATLAB代码
原文地址:https://blog.csdn.net/weixin_46204734/article/details/134718596
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