一、大甘蔗鼠算法
大甘蔗鼠算法（Greater Cane Rat Algorithm，GCRA）由Jeffrey O. Agushaka等人于2024年提出，该算法模拟大甘蔗鼠的智能觅食行为。
参考文献
[1]Agushaka J O, Ezugwu A E, Saha A K, et al. Greater Cane Rat Algorithm (GCRA): A Nature-Inspired Metaheuristic for Optimization Problems[J]. Heliyon, 2024.
二、23个函数介绍
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='F8'; % 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]=GCRA(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('GCRA')
saveas(gca,[Function_name '.jpg']);
display(['The best solution is ', num2str(Best_pos)]);
display(['The best fitness value is ', num2str(Best_fit)]);
四、部分结果
