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⛄ 内容介绍
This paper proposes a novel nature-inspired meta-heuristic optimizer, called Reptile Search Algorithm (RSA), motivated by the hunting behaviour of Crocodiles. Two main steps of Crocodile behaviour are implemented, such as encircling, which is performed by high walking or belly walking, and hunting, which is performed by hunting coordination or hunting cooperation. The mentioned search methods of the proposed RSA are unique compared to other existing algorithms. The performance of the proposed RSA is evaluated using twenty-three classical test functions, thirty CEC2017 test functions, ten CEC2019 test functions, and seven real-world engineering problems. The obtained results of the proposed RSA are compared to various existing optimization algorithms in the literature. The results of the tested three benchmark functions revealed that the proposed RSA achieved better results than the other competitive optimization algorithms. The results of the Friedman ranking test proved that the RSA is a significantly superior method than other comparative methods. Finally, the results of the examined engineering problems showed that the RSA obtained better results compared to other various methods.
⛄ 部分代码
%_______________________________________________________________________________________%
% Reptile Search Algroithm (RSA) source codes demo version 1.0 %
% %
% Developed in MATLAB R2015a (7.13) %
% %
% Author and programmer: Laith Abualigah %
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% e-Mail: Aligah.2020@gmail.com %
% Homepage: %
% 1- https://scholar.google.com/citations?user=39g8fyoAAAAJ&hl=en %
% 2- https://www.researchgate.net/profile/Laith_Abualigah %
%_______________________________________________________________________________________%
% Main paper: Reptile Search Algorithm (RSA): %
% A novel nature-inspired meta-heuristic optimizer % %
%_______________________________________________________________________________________%
clear all
clc
Solution_no=50; %Number of search solution
F_name='F3'; %Name of the test function
T=100; %Maximum number of iterations
[LB,UB,Dim,F_obj]=Get_F(F_name); %Give details of the underlying benchmark functions
[Best_F,Best_P,Conv]=RSA(Solution_no,T,LB,UB,Dim,F_obj); % Call Reptile Search Algorithm (RSA)
figure('Position',[454 445 694 297]);
subplot(1,2,1);
func_plot(F_name); % Function plot
title('Parameter space')
xlabel('x_1');
ylabel('x_2');
zlabel([F_name,'( x_1 , x_2 )'])
subplot(1,2,2); % Convergance plot
plot(Conv,'LineWidth',3)
xlabel('Iteration#');
ylabel('Best fitness function');
legend('RSA');
display(['The best-obtained solution by RSA is : ', num2str(Best_P)]);
display(['The best optimal value of the objective funciton found by RSA is : ', num2str(Best_F)]);
⛄ 运行结果
⛄ 参考文献
[1] Abualigah, L. , et al. "Reptile Search Algorithm (RSA): A nature-inspired meta-heuristic optimizer." Expert Systems with Applications 191(2022):116158-.
