# 基于动态控制布谷鸟算法求解单目标优化问题（DDCS)附matlab代码

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## ⛄ 部分代码

% Dynamic control Cuckoo search (DCCS) source Code Version 1.0

%

% Developed in MATLAB R2018b

%

% Author and programmer:

% Dr Manoj Kumar Naik

% Faculty of Engineering and Technology, Siksha O Anusandhan, Bhubaneswar, Odisha 鈥� 751030, India

% e-mail:       naik.manoj.kumar@gmail.com

% Researchgate: https://www.researchgate.net/profile/Manoj_Naik9

%_____________________________________________________________________________________________________

% Please cite to the main paper:

% M.K. Naik, M. Swain, R. Panda, A. Abraham,

% An Evolutionary Dynamic Control Cuckoo Search Algorithm for Solving the Constrained Engineering Design Problems,

% Int. J. Swarm Intell. Res. 13 (2022) 1�25.

%__________________________________________________________________________________________________

clearvars

close all

clc

disp('The DCCS is tracking the problem');

N=30; % Number of Cuckoo

Function_name='F12' % Name of the test function that can be from F1 to F23

MaxIT=500; % Maximum number of iterations

[lb,ub,dim,fobj]=Get_Functions_details(Function_name); % Function details

Times=11; %Number of independent times you want to run the DCCS

display(['Number of independent runs: ', num2str(Times)]);

for i=1:Times

[Destination_fitness(i),bestPositions(i,:),Convergence_curve(i,:)]=DCCS(N,MaxIT,lb,ub,dim,fobj);

display(['The optimal fitness of DCCS is: ', num2str(Destination_fitness(i))]);

end

[bestfitness,index]=min(Destination_fitness);

disp('--------Best Fitness, Average Fitness, Standard Deviation and Best Solution--------');

display(['The best fitness of DCCS is: ', num2str(bestfitness)]);

display(['The average fitness of DCCS is: ', num2str(mean(Destination_fitness))]);

display(['The standard deviation fitness of DCCS is: ', num2str(std(Destination_fitness))]);

display(['The best location of DCCS is: ', num2str(bestPositions(index,:))]);

figure('Position',[454   445   694   297]);

subplot(1,2,1);

func_plot(Function_name);

title('Parameter space')

xlabel('x_1');

ylabel('x_2');

zlabel([Function_name,'( x_1 , x_2 )'])

subplot(1,2,2);

semilogy(Convergence_curve(index,:),'LineWidth',3);

xlabel('Iterations');

ylabel('Best fitness obtained so far');

legend('DCCS');

box on;

axis tight;

grid off;

## ⛄ 参考文献

[1]尚志勇．基于改进布谷鸟搜索算法的配发中心选址问题研究。（博士论文，河南大学）。

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