一、算法介绍
鳗鱼和石斑鱼优化器(Eel and grouper optimizer,EGO)是2024年提出的一种智能优化算法,EGO算法的灵感来自海洋生态系统中鳗鱼和石斑鱼的共生相互作用和觅食策略。
参考文献:
[1]A. Mohammadzadeh, S. Mirjalili, Eel and Grouper Optimizer: A Nature-inspired Optimization Algorithm, Cluster Computing , in press, 2024DOI: Eel and grouper optimizer: a nature-inspired optimization algorithm | Cluster Computing
二、23个函数简介
参考文献:
[1] Yao X, Liu Y, Lin G M. Evolutionary programming made faster[J]. IEEE transactions on evolutionary computation, 1999, 3(2):82-102.
三、部分代码
close all ; clear clc Npop=30; Function_name='F1'; % Name of the test function that can be from F1 to F23 ( Tmax=300; [lb,ub,dim,fobj]=Get_Functions_details(Function_name); [Best_fit,Best_pos,Convergence_curve]=(Npop,Tmax,lb,ub,dim,fobj); figure('Position',[100 100 660 290]) %Draw search space subplot(1,2,1); func_plot(Function_name); title('Parameter space') xlabel('x_1'); ylabel('x_2'); zlabel([Function_name,'( x_1 , x_2 )']) %Draw objective space subplot(1,2,2); semilogy(Convergence_curve,'Color','r','linewidth',3) title('Search space') xlabel('Iteration'); ylabel('Best score obtained so far'); axis tight grid on box on legend('') saveas(gca,[Function_name '.jpg']); display(['The best solution is ', num2str(Best_pos)]); display(['The best fitness value is ', num2str(Best_fit)]);