clc;
clear;
close all;
warning off;
addpath(genpath(pwd));
rng('default');
% Problem Statement
Npar = 3;
VarLow=[-5.12 -5.12 -5.12];
VarHigh = [5.12 5.12 5.12];
% parameters
MaxIter=100; %Maximum iteration
N=50; %Initial population
c1 = 20;
c2 =0.003;
mp =0.6;
B = 1;
% initialize a random value as best value
XBest = rand(1,Npar).* (VarHigh - VarLow) + VarLow;
XBestCost = fitnessFunc(XBest);
GB = XBestCost;
t=cputime;
% Initialize of magnetotatic bacteria and memory
X = zeros(N,Npar);
F = zeros(N, 1);
Fnorm = F;
for ii=1:N
% initialize with a random solution
X(ii,:)=rand(1,Npar) .* (VarHigh - VarLow) + VarLow;
% find the fitness of the solution
F(ii)=fitnessFunc(X(ii,:));
end
% Main Loop
for it=1:MaxIter
rng(it);
%normalized fitnesss
for ii= 1:N
Fnorm(ii) = (F(ii) - min(F))/(max(F) - min(F));
end
%interaction distance
for ii = 1:N
for jj = 1:N
for kk = 1:Npar
D(ii,jj,kk) = (X(ii,kk) - X(jj,kk));
end
end
end
%Moments
for ii = 1:N
for jj=1:N
for kk = 1:Npar
p = round(rand*N +0.5);
q = round(rand*N +0.5);
for dd = 1:Npar
DD(dd) = D(ii,jj,dd);
end
E(ii,jj,kk) = (D(ii,jj,kk)/(1+c1*norm(DD) + c2*D(p,q)))^3;
end
end
end
M = E/B;
%moment regulation
for ii=1:N
if (rand<mp)
X(ii,:) = X(ii,:) + (XBest - X(ii,:)).*rand(1,Npar);
else
for jj = 1:Npar
r = round(rand*N +0.5);
X(ii,jj) = X(r,jj);
end
end
% limit solution within search space
X(ii,:) = limiter(X(ii,:),VarHigh,VarLow);
% find new fitness
F(ii) = fitnessFunc(X(ii,:));
end
%MTS Replacement
[F, sortOrder] = sort(F);
X = X(sortOrder,:);
for ii= round(N/2):N
if rand<0.5
for jj = 1:Npar
r = round(rand*N +0.5);
X(ii,jj) = X(ii,jj) + rand*M(ii,r,jj);
end
else
X(ii,:)=rand(1,Npar) .* (VarHigh - VarLow) + VarLow;
end
% limit solution within search space
X(ii,:) = limiter(X(ii,:),VarHigh,VarLow);
% find new fitness
F(ii) = fitnessFunc(X(ii,:));
end
[F, sortOrder] = sort(F);
X = X(sortOrder,:);
if (F(1) < XBestCost)
XBestCost = F(1);
XBest = X(1,:);
end
% store the best value in each iteration
GB=[GB XBestCost];
end
t1=cputime;
fprintf('The time taken is %3.2f seconds \n',t1-t);
fprintf('The best value is :');
XBest
XBestCost
figure
plot(0:MaxIter,GB, 'linewidth',1.2);
xlabel('Iterations');
ylabel('Objective Function (Cost)');
grid('on')
