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
参考文献：
[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
无人机飞行路径坐标：
1.0000000e+01 1.0000000e+01 8.0000000e+01 1.0951749e+01 1.0964931e+01 8.0886341e+01 1.1866404e+01 1.1859602e+01 8.1735889e+01 1.2745345e+01 1.2686798e+01 8.2550078e+01 1.3589950e+01 1.3449305e+01 8.3330341e+01 1.4401601e+01 1.4149907e+01 8.4078111e+01 1.5181676e+01 1.4791390e+01 8.4794821e+01 1.5931554e+01 1.5376539e+01 8.5481904e+01 1.6652617e+01 1.5908138e+01 8.6140794e+01 1.7346242e+01 1.6388973e+01 8.6772924e+01 1.8013811e+01 1.6821828e+01 8.7379727e+01 1.8656702e+01 1.7209490e+01 8.7962636e+01 1.9276295e+01 1.7554743e+01 8.8523085e+01 1.9873969e+01 1.7860371e+01 8.9062506e+01 2.0451105e+01 1.8129161e+01 8.9582333e+01 2.1009082e+01 1.8363897e+01 9.0084000e+01 2.1549279e+01 1.8567364e+01 9.0568939e+01 2.2073077e+01 1.8742348e+01 9.1038583e+01 2.2581854e+01 1.8891632e+01 9.1494366e+01 2.3076991e+01 1.9018004e+01 9.1937721e+01 2.3559867e+01 1.9124247e+01 9.2370082e+01 2.4031861e+01 1.9213146e+01 9.2792881e+01 2.4494353e+01 1.9287488e+01 9.3207551e+01 2.4948724e+01 1.9350056e+01 9.3615527e+01 2.5396352e+01 1.9403636e+01 9.4018240e+01 2.5838617e+01 1.9451013e+01 9.4417125e+01 2.6276898e+01 1.9494971e+01 9.4813614e+01 2.6712576e+01 1.9538297e+01 9.5209141e+01 2.7147030e+01 1.9583775e+01 9.5605139e+01 2.7581640e+01 1.9634191e+01 9.6003041e+01 2.8017785e+01 1.9692328e+01 9.6404281e+01 2.8456844e+01 1.9760973e+01 9.6810291e+01 2.8900198e+01 1.9842910e+01 9.7222505e+01 2.9349226e+01 1.9940925e+01 9.7642356e+01 2.9805307e+01 2.0057802e+01 9.8071277e+01 3.0269822e+01 2.0196327e+01 9.8510701e+01 3.0744150e+01 2.0359285e+01 9.8962062e+01 3.1229670e+01 2.0549461e+01 9.9426794e+01 3.1727763e+01 2.0769639e+01 9.9906328e+01 3.2239807e+01 2.1022605e+01 1.0040210e+02 3.2767182e+01 2.1311145e+01 1.0091554e+02 3.3311269e+01 2.1638042e+01 1.0144808e+02 3.3873446e+01 2.2006083e+01 1.0200116e+02 3.4455093e+01 2.2418051e+01 1.0257621e+02 3.5057590e+01 2.2876733e+01 1.0317466e+02 3.5682316e+01 2.3384914e+01 1.0379794e+02 3.6330652e+01 2.3945378e+01 1.0444750e+02 3.7003976e+01 2.4560910e+01 1.0512476e+02 3.7703668e+01 2.5234296e+01 1.0583115e+02 3.8431109e+01 2.5968321e+01 1.0656811e+02 3.9187677e+01 2.6765769e+01 1.0733707e+02 3.9974752e+01 2.7629427e+01 1.0813947e+02 4.0793714e+01 2.8562078e+01 1.0897673e+02 4.1645942e+01 2.9566508e+01 1.0985030e+02 4.2532816e+01 3.0645502e+01 1.1076160e+02 4.3455716e+01 3.1801845e+01 1.1171207e+02 4.4416021e+01 3.3038322e+01 1.1270314e+02 4.5415111e+01 3.4357719e+01 1.1373624e+02 4.6454365e+01 3.5762820e+01 1.1481281e+02 4.7535163e+01 3.7256410e+01 1.1593428e+02 4.8658886e+01 3.8841275e+01 1.1710209e+02 4.9826911e+01 4.0520199e+01 1.1831766e+02 5.1040619e+01 4.2295968e+01 1.1958244e+02 5.2301390e+01 4.4171367e+01 1.2089784e+02 5.3610603e+01 4.6149180e+01 1.2226532e+02 5.4969638e+01 4.8232193e+01 1.2368629e+02 5.6379875e+01 5.0423191e+01 1.2516219e+02 5.7842692e+01 5.2724959e+01 1.2669447e+02 5.9359470e+01 5.5140282e+01 1.2828454e+02 6.0931588e+01 5.7671946e+01 1.2993384e+02 6.2560426e+01 6.0322734e+01 1.3164381e+02 6.4247364e+01 6.3095433e+01 1.3341588e+02 6.5993780e+01 6.5992827e+01 1.3525149e+02 6.7801056e+01 6.9017701e+01 1.3715205e+02 6.9670570e+01 7.2172841e+01 1.3911902e+02 7.1603701e+01 7.5461031e+01 1.4115382e+02 7.3601831e+01 7.8885057e+01 1.4325788e+02 7.5666337e+01 8.2447704e+01 1.4543265e+02 7.7798600e+01 8.6151757e+01 1.4767954e+02 8.0000000e+01 9.0000000e+01 1.5000000e+02
四、完整MATLAB代码
