一、火鹰优化算法FHO
火鹰优化算法(Fire Hawk Optimizer,FHO)由Mahdi Azizi等人于2022年提出,该算法性能高效,思路新颖。
单目标优化:火鹰优化算法(Fire Hawk Optimizer,FHO)求解cec2020(提供Matlab代码)-CSDN博客
参考文献:
[1]Azizi, M., Talatahari, S. & Gandomi, A.H. Fire Hawk Optimizer: a novel metaheuristic algorithm. Artif Intell Rev (2022). Fire Hawk Optimizer: a novel metaheuristic algorithm | Artificial Intelligence Review:
二、23个基本函数简介
三、FHO求解23个函数
(1)部分代码
clear all; close all; clc; Function_name = 'F1'; % function name Npop = 50; % Number of search agents Max_it = 100; % Maximum number of iterations [lb,ub,nD,fobj]=Get_Functions_details(Function_name); [fvalbest,xposbest,Curve]=FHO(Npop,Max_it,lb,ub,nD,fobj); semilogy(Curve,'linewidth',2); legend('FHO') title(Function_name) xlabel('t') ylabel('f') figure func_plot(Function_name); title(Function_name) xlabel('x_1'); ylabel('x_2'); zlabel([Function_name,'( x_1 , x_2 )'])
(2)部分结果