Index exceeds matrix dimensions.

7 views (last 30 days)
tahseen alshmary
tahseen alshmary on 4 Dec 2018
Answered: tahseen alshmary on 4 Dec 2018
Dear sirs
i have this error with PSO code below any one can help me
the error is
Index exceeds matrix dimensions.
Error in ofun (line 92)
f=alph1*(of)^2+alph2*(DT-beta(2)*(DT- abs(DT)))^2; % fitness function
Error in Untitled4 (line 32)
f0{i}=ofun(x0(i,:));
the code is
%Save the following codes in MATLAB script file (*.m) and save as ofun.m.
%----------------------------------------------------------------------------------------------------------------------------------start
function f=ofun(x) % objective function (minimization)
of =2.633*x(1)+2.992*x(2)+3.134*x(3)+3.678*x(4)+3.620*x(5)+2.948*x(6)+1.607*x(7)+2.952*x(8)+3.348*x(9)+3.680*x(10)+3.774*x(11)+2.995*x(12)+3.237*x(13)+1.608*x(14);
% if there is no constraints then comments all c0 lines below
c =[];
CTI =0.3;
A(1) =2.633*x(1); B(1) =4.112*x(6); %first row
A(2) =2.992*x(2); B(2) =4.870*x(1); %second row
A(3) =2.992*x(2); B(3) =2.178*x(7); %third row
A(4) =3.134*x(3); B(4) =3.857*x(2); %fourth row
A(5) =3.678*x(4); B(5) =3.989*x(3); %fifth row
A(6) =3.620*x(5); B(6) =4.979*x(4); %sixth row
A(7) =2.948*x(6); B(7) =5.756*x(5); %seventh row
A(8) =1.607*x(7); B(8) =5.826*x(5); %eighth row
A(9) =2.948*x(6); B(9) =2.150*x(14); %nighth row
A(10)=1.607*x(7); B(10)=6.920*x(13); %tenth row
A(11)=2.952*x(8); B(11)=2.144*x(7); %eleventh row
A(12)=2.952*x(8); B(12)=5.365*x(9); %tweleventh row
A(13)=3.348*x(9); B(13)=4.863*x(10); %thirteenth row
A(14)=3.680*x(10); B(14)=5.073*x(11); %fourteenth row
A(15)=3.774*x(11); B(15)=3.774*x(12); %fiveteenth row
A(16)=2.995*x(12); B(16)=6.920*x(13); %sixteenth row
A(17)=2.995*x(12); B(17)=2.151*x(14); %seventennth row
A(18)=3.237*x(13); B(18)=4.288*x(8); %eighteenth row
A(19)=1.608*x(14); B(19)=4.870*x(1); %nighnteenth row
A(20)=1.608*x(14); B(20)=5.365*x(9); % twenty row
for I = 1:length (A)
for J = 1:length (B)
DT(I,J) = B(J)-A(I)-CTI;
if DT(I,J)>=0
D(I,J)=0;
else
D(I,J)= B(J)-A(I)+CTI;
end
end
end
c0(1)= B(1) -A(1)-CTI;
c0(2)= B(2) -A(2)-CTI;
c0(3)= B(3) -A(3)-CTI;
c0(4)= B(4) -A(4)-CTI;
c0(5)= B(5) -A(5)-CTI;
c0(6)= B(6) -A(6)-CTI;
c0(7)= B(7) -A(7)-CTI;
c0(8)= B(8) -A(8)-CTI;
c0(9)= B(9) -A(9)-CTI;
c0(10)= B(10)-A(10)-CTI;
c0(11)= B(11)-A(11)-CTI;
c0(12)= B(12)-A(12)-CTI;
c0(13)= B(13)-A(13)-CTI;
c0(14)= B(14)-A(14)-CTI;
c0(15)= B(15)-A(15)-CTI;
c0(16)= B(16)-A(16)-CTI;
c0(17)= B(17)-A(17)-CTI;
c0(18)= B(18)-A(18)-CTI;
c0(19)= B(19)-A(19)-CTI;
c0(20)= B(20)-A(20)-CTI;
for d = 1: length(c0)
if c0(d)>=0
c(d)=0;
else
c(d)=1;
end
end
alph1=1;
alph2=2;
beta = 100;
f=alph1*(of)^2+alph2*(DT-beta(2)*(DT- abs(DT)))^2; % fitness function
%---------------------------------------------------------------------------------------------end
%---------------------------------------------------------------------------------------------------------------------------------start
tic
clc
clear all
close all
rng default
LB=[0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05]; % lower bounds of variables
UB=[1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1]; % upper bounds of variables
% pso parameters values
m=14; % number of variables
n=100; % population size
wmax=0.9; % inertia weight
wmin=0.4; % inertia weight
c1=2; % acceleration factor
c2=2; % acceleration factor
% pso main program----------------------------------------------------start
maxite=500; % set maximum number of iteration
maxrun=10; % set maximum number of runs need to be
for run=1:maxrun
run
% pso initialization----------------------------------------------start
for i=1:n
for j=1:m
x0(i,j)=round(LB(j)+rand()*(UB(j)-LB(j)));
end
end
x=x0; % initial population
v=0.1*x0; % initial velocity
f0=cell(1,n); %preallocation
for i=1:n
f0{i}=ofun(x0(i,:));
end
[fmin0,index0]=min(f0{i});
pbest=x0; % initial pbest
gbest=x0(index0,:); % initial gbest
% pso initialization-----------------------------------------------end
% pso algorithm---------------------------------------------------start
ite=1;
tolerance=1;
while ite<=maxite
tolerance>1e-12
w=wmax-(wmax-wmin)*ite/maxite; % update inertial weight
% pso velocity updates
for i=1:n
for j=1:m
v(i,j)=w*v(i,j)+c1*rand()*(pbest(i,j)-x(i,j))...
+c2*rand()*(gbest(1,j)-x(i,j));
end
end
% pso position update
for i=1:n
for j=1:m
x(i,j)=x(i,j)+v(i,j);
end
end
% handling boundary violations
for i=1:n
for j=1:m
if x(i,j)<LB(j)
x(i,j)=LB(j);
elseif x(i,j)>UB(j)
x(i,j)=UB(j);
end
end
end
% evaluating fitness
f=cell(1,50); %preallocation
for i=1:n
f{i}=ofun(x(i,:));
end
% updating pbest and fitness
for i=1:n
if f{i}<f0{i}
pbest(i,:)=x(i,:);
f0{i}=f{i};
end
end
[fmin,index]=min(f0{i});
% finding out the best particle
ffmin(ite,run)=fmin(1); % storing best fitness
ffite(run)=ite; % storing iteration count
% updating gbest and best fitness
if fmin<fmin0
gbest=pbest(index,:);
fmin0=fmin;
end
% calculating tolerance
if ite>100;
tolerance=abs(ffmin(ite-100,run)-fmin0);
end
% displaying iterative results
if ite==1
fprintf('Iteration Best particle Objective fun\n');
end
fprintf('%8g %8g %8.4f\n',ite,index,fmin0);
ite=ite+1;
end
% pso algorithm---------------------------------------------------end
gbest
fvalue=2.633*x(1)+2.992*x(2)+3.134*x(3)+3.678*x(4)+3.620*x(5)+2.948*x(6)+1.607*x(7)+2.952*x(8)+3.348*x(9)+3.680*x(10)+3.774*x(11)+2.995*x(12)+3.237*x(13)+1.608*x(14);
fff(run)=fvalue
rgbest(run,:)=gbest;
fprintf('--------------------------------------\n');
end
% pso main program------------------------------------------------------end
fprintf('\n\n');
fprintf('*********************************************************\n');
fprintf('Final Results-----------------------------\n');
[bestfun,bestrun]=min(fff)
best_variables=rgbest(bestrun,:)
fprintf('*********************************************************\n');
toc
% PSO convergence characteristic
plot(ffmin(1:ffite(bestrun),bestrun),'-k');
xlabel('Iteration');
ylabel('Fitness function value');
title('PSO convergence characteristic')
% checking for coordination time interval (CTI)
CTI1 = -2.633*best_variables(1) + 4.112*best_variables(6)
CTI2 = +4.870*best_variables(1) - 2.992*best_variables(2)
CTI3 = -2.992*best_variables(2) + 2.178*best_variables(7)
CTI4 = +3.857*best_variables(2) - 3.134*best_variables(3)
CTI5 = +3.989*best_variables(3) - 3.678*best_variables(4)
CTI6 = +4.979*best_variables(4) - 3.620*best_variables(5)
CTI7 = +5.756*best_variables(5) - 2.948*best_variables(6)
CTI8 = +5.826*best_variables(5) - 1.607*best_variables(7)
CTI9 = -2.948*best_variables(6) + 2.150*best_variables(14)
CTI10= -1.607*best_variables(7) + 6.920*best_variables(13)
CTI11= +2.144*best_variables(7) - 2.952*best_variables(8)
CTI12= -2.952*best_variables(8) + 5.365*best_variables(9)
CTI13= -3.348*best_variables(9) + 4.863*best_variables(10)
CTI14= -3.680*best_variables(10)+ 5.073*best_variables(11)
CTI15= -3.774*best_variables(11)+ 3.774*best_variables(12)
CTI16= -2.995*best_variables(12)+ 6.920*best_variables(13)
CTI17= -2.995*best_variables(12)+ 2.151*best_variables(14)
CTI18= +4.288*best_variables(8) - 3.237*best_variables(13)
CTI19= +4.870*best_variables(1) - 1.608*best_variables(14)
CTI20= +5.365*best_variables(9) - 1.608*best_variables(14)
%##########################################--------------------------end

Answers (1)

tahseen alshmary
tahseen alshmary on 4 Dec 2018
Any one know where is the problem? please

Products


Release

R2017b

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by