一、孟加拉虎优化算法
孟加拉虎优化（ Savannah Bengal Tiger Optimization ，SBTO）算法模拟了孟加拉虎的群体狩猎行为，采用了猎物搜索、隐身接近和攻击狩猎三种策略。
参考文献：
1\]Yujing Sun, Xingguo Xu. Savannah Bengal Tiger Optimization (SBTO): A Novel Metaheuristic Algorithm for Constrained Optimization Problems, 29 October 2024, PREPRINT (Version 1) available at Research Square https://doi.org/10.21203/rs.3.rs-5298106/v1 ### 二、无人机模型介绍 [单个无人机三维路径规划问题及其建模](https://blog.csdn.net/weixin_46204734/article/details/132482288?spm=1001.2014.3001.5502) 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 ### 三、路径规划MATLAB ```dart 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=100; % 种群大小(可以修改) Function_name='F2'; %F1:随机产生地图 F2：导入固定地图 Max_iteration=100; %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); ```  部分路径点坐标： 1.0000000e+01 1.0000000e+01 8.0000000e+01 1.1904074e+01 1.1230847e+01 8.1530987e+01 1.3768975e+01 1.2460413e+01 8.3041101e+01 1.5595212e+01 1.3688531e+01 8.4530513e+01 1.7383295e+01 1.4915033e+01 8.5999391e+01 1.9133733e+01 1.6139751e+01 8.7447903e+01 2.0847036e+01 1.7362516e+01 8.8876219e+01 2.2523712e+01 1.8583161e+01 9.0284508e+01 2.4164270e+01 1.9801517e+01 9.1672939e+01 2.5769220e+01 2.1017417e+01 9.3041679e+01 2.7339072e+01 2.2230691e+01 9.4390900e+01 2.8874333e+01 2.3441173e+01 9.5720769e+01 3.0375515e+01 2.4648693e+01 9.7031455e+01 3.1843125e+01 2.5853084e+01 9.8323127e+01 3.3277673e+01 2.7054179e+01 9.9595955e+01 3.4679668e+01 2.8251807e+01 1.0085011e+02 3.6049620e+01 2.9445803e+01 1.0208575e+02 3.7388038e+01 3.0635997e+01 1.0330306e+02 3.8695430e+01 3.1822221e+01 1.0450219e+02 3.9972307e+01 3.3004307e+01 1.0568333e+02 4.1219177e+01 3.4182088e+01 1.0684664e+02 4.2436550e+01 3.5355395e+01 1.0799228e+02 4.3624934e+01 3.6524059e+01 1.0912043e+02 4.4784840e+01 3.7687914e+01 1.1023126e+02 4.5916776e+01 3.8846790e+01 1.1132493e+02 4.7021251e+01 4.0000521e+01 1.1240161e+02 4.8098776e+01 4.1148936e+01 1.1346148e+02 4.9149858e+01 4.2291869e+01 1.1450469e+02 5.0175008e+01 4.3429152e+01 1.1553143e+02 5.1174734e+01 4.4560616e+01 1.1654186e+02 5.2149545e+01 4.5686093e+01 1.1753614e+02 5.3099952e+01 4.6805415e+01 1.1851445e+02 5.4026463e+01 4.7918414e+01 1.1947696e+02 5.4929587e+01 4.9024922e+01 1.2042383e+02 5.5809834e+01 5.0124771e+01 1.2135524e+02 5.6667712e+01 5.1217793e+01 1.2227134e+02 5.7503732e+01 5.2303819e+01 1.2317232e+02 5.8318402e+01 5.3382682e+01 1.2405834e+02 5.9112231e+01 5.4454213e+01 1.2492957e+02 5.9885730e+01 5.5518244e+01 1.2578618e+02 6.0639406e+01 5.6574608e+01 1.2662833e+02 6.1373770e+01 5.7623136e+01 1.2745621e+02 6.2089330e+01 5.8663660e+01 1.2826996e+02 6.2786595e+01 5.9696011e+01 1.2906977e+02 6.3466076e+01 6.0720023e+01 1.2985581e+02 6.4128280e+01 6.1735526e+01 1.3062823e+02 6.4773718e+01 6.2742353e+01 1.3138722e+02 6.5402899e+01 6.3740336e+01 1.3213293e+02 6.6016332e+01 6.4729306e+01 1.3286555e+02 6.6614525e+01 6.5709095e+01 1.3358523e+02 6.7197989e+01 6.6679535e+01 1.3429215e+02 6.7767232e+01 6.7640459e+01 1.3498647e+02 6.8322764e+01 6.8591698e+01 1.3566837e+02 6.8865094e+01 6.9533083e+01 1.3633801e+02 6.9394732e+01 7.0464448e+01 1.3699557e+02 6.9912185e+01 7.1385623e+01 1.3764120e+02 7.0417965e+01 7.2296441e+01 1.3827509e+02 7.0912579e+01 7.3196733e+01 1.3889739e+02 7.1396537e+01 7.4086332e+01 1.3950828e+02 7.1870349e+01 7.4965070e+01 1.4010793e+02 7.2334523e+01 7.5832777e+01 1.4069651e+02 7.2789569e+01 7.6689287e+01 1.4127417e+02 7.3235996e+01 7.7534431e+01 1.4184111e+02 7.3674314e+01 7.8368040e+01 1.4239747e+02 7.4105031e+01 7.9189948e+01 1.4294344e+02 7.4528656e+01 7.9999985e+01 1.4347918e+02 7.4945700e+01 8.0797984e+01 1.4400486e+02 7.5356671e+01 8.1583777e+01 1.4452064e+02 7.5762078e+01 8.2357195e+01 1.4502670e+02 7.6162431e+01 8.3118071e+01 1.4552321e+02 7.6558238e+01 8.3866235e+01 1.4601034e+02 7.6950010e+01 8.4601521e+01 1.4648824e+02 7.7338255e+01 8.5323760e+01 1.4695710e+02 7.7723483e+01 8.6032784e+01 1.4741709e+02 7.8106203e+01 8.6728425e+01 1.4786836e+02 7.8486923e+01 8.7410515e+01 1.4831109e+02 7.8866154e+01 8.8078886e+01 1.4874545e+02 7.9244404e+01 8.8733369e+01 1.4917161e+02 7.9622183e+01 8.9373796e+01 1.4958974e+02 8.0000000e+01 9.0000000e+01 1.5000000e+02 ### 四、完整MATLAB见下方名片