could anyone help me how to solve the error for the following code

code:

tic
clc
clear all
close all
rng default 
LB=[0 0 0 ];         %lower bounds of variables
UB=[10 10 10 ];      %upper bounds of variables 
% pso parameters values 
m=3;            % number of variables
n=4;          % 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=10;    % set maximum number of iteration
maxrun=5;      % set maximum number of runs need to be
for run=1:maxrun   
   run  ;
   Z=run;% pso initialization----------------------------------------------start  
    for i=1:n 
        A=i;
                for j=1:m
                    B=j;
                    C=rand();
                    E=LB(j);
            F=UB(j);
            G=round(LB(j)+C*(UB(j)-LB(j)));
            
            x0(i,j)=round(LB(j)+C*(UB(j)-LB(j)));
            D=x0(i,j);
        end
    end
    x=x0;       % initial population  
    v=0.1*x0;   % initial velocity 
    for i=1:n 
        Y=i;
        f0(i,1)=ofun(x0(i,:));  
    end
    [fmax0,index0]=max(f0) ;     
    pbest=x0  ;            % initial pbest 
    gbest=x0(index0,:) ;    % initial gbest 
    % pso initialization------------------------------------------------end        
    % pso algorithm---------------------------------------------------start 
    ite=1 ;
    tolerance=1 ;
    while ite>=maxite && tolerance<10^-12 
        YY=ite<=maxite && tolerance>10^-12 
    w=wmax-(wmax-wmin)*ite/maxite;% update inertial weight     
    % pso velocity updates   
    for i=1:n        
        for j=1:m 
            t=v(i,j);
            r=rand();
            ss=pbest(i,j);
            rr=x(i,j);
            k=rand();
            kk=gbest(1,j);
            v(i,j)=w*t+c1*r*(pbest(i,j)-x(i,j))... 
                +c2*k*(gbest(1,j)-x(i,j));
            
            V=v(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    
    for i=1:n      
        f(i,1)=ofun(x(i,:));
    end
    % updating pbest and fitness   
    for i=1:n        
        if f(i,1)>f0(i,1)
            pbest(i,:)=x(i,:) ;    
            f0(i,1)=f(i,1)  ;    
        end
    end
    [fmax,index]=max(f0) ;  % finding out the best particle     
    ffmax(ite,run)=fmax;  % storing best fitness      
    ffite(run)=ite;      % storing iteration count
    % updating gbest and best fitness   
    AA=fmax;
        BB=fmax0;
    if fmax>fmax0 
%         CC=pbest(index,:) 
        gbest=pbest(index,:);    
        
        fmax0=fmax;  
    end 
    % calculating tolerance     
    if ite<100;         
        tolerance=abs(ffmax(ite-100,run)-fmax0) ;   
    end
    % displaying iterative results    
    if ite==1      
        disp(sprintf('Iteration    Best particle    Objective fun'));  
    end
    disp(sprintf('%8g  %8g   %8.4f',ite,index,fmax0))  ;  
    ite=ite+1;
    end
    % pso algorithm-----------------------------------------------------end 
    gbest ;
    fvalue=10*(gbest(1)-1)^2+20*(gbest(2)-2)^2+30*(gbest(3)-3)^2 ; 
    fff(run)=fvalue;
    rgbest(run,:)=gbest ;  
    disp(sprintf('--------------------------------------'))
end
% pso main program------------------------------------------------------end 
%  disp(sprintf('\n')) ; %create space or gap
% disp(sprintf('*********************************************************')); 
% disp(sprintf('Final Results-----------------------------'));
[bestfun,bestrun]=max(fff)
best_variables=rgbest(bestrun,:) 
% disp(sprintf('*********************************************************')); 
toc
% PSO convergence characteristic
 
plot(ffmax(1:ffite(bestrun),bestrun),'-*b') 
xlabel('Iteration')
ylabel('Fitness  value')
title('PSO convergence')

when i run the code it gives error stating Undefined function or variable 'ffite'.

Error in line 134 plot(ffmax(1:ffite(bestrun),bestrun),'-*b').

Could anyone please help me on this.

[KSSV]

Undefined function or variable 'ofun'.

[jaah navi]

this was the function which I have used for the above code to execute

 function f=ofun(x)  
% objective function (minimization)
% x=9
% x0(i,j)=round(LB(j)+C*(UB(j)-LB(j)))
 of=10*(x(1)-1)^2+20*(x(2)-2)^2+30*(x(3)-3)^2;
 a=x(1);
 b=x(2);
 c=x(3);
% of=8*(x-1)^2+16*(x-2)^2+24*(x-3)^2
% constraints (all constraints must be converted into <=0 type)
% if there is no constraints then comments all c0 lines below 
c0=[] ;
c0(1)=x(1)+x(2)+x(3)-5  ;   % <=0 type constraints 
c0(2)=x(1)^2+2*x(2)-x(3) ;  % <=0 type constraints
%  c0(1)=x+x+x-5     % <=0 type constraints 
%  c0(2)=-x^2+2*x-x   % <=0 type constraints
%  c0(3)=-x^3


% defining penalty for each constraint
for i=1:length(c0)
    p=i;
    if c0(i)>0  
        q=c0(i);
        c(i)=1 ;
        r=c(i);
    else
        c(i)=0; 
        s=c(i);
    end
end
penalty=10000;
u=c;
t=sum(c);% penalty on each constraint violation
f=of+penalty*sum(c)   ; % fitness function
 end

Answer 1

[KSSV]

ffite is defined inside while loop.......your code is not entering inside the while loop......so ffite is not defined......you need to change the conditions of while loop.

[jaah navi]

I have changed the condition but still i am getting the same error for the below code

tic

clc

clear all

close all

rng default

LB=[0 0 0 ]; %lower bounds of variables

UB=[10 10 10 ]; %upper bounds of variables

% pso parameters values

m=3; % 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=1000; % set maximum number of iteration

maxrun=10; % set maximum number of runs need to be

for run=1:maxrun

run ;

Z=run;% pso initialization----------------------------------------------start

for i=1:n

A=i;

for j=1:m

B=j;

C=rand();

E=LB(j);

F=UB(j);

G=round(LB(j)+C*(UB(j)-LB(j)));

x0(i,j)=round(LB(j)+C*(UB(j)-LB(j)));

D=x0(i,j);

end

end

x=x0; % initial population

v=0.1*x0; % initial velocity

for i=1:n

Y=i;

f0(i,1)=ofun(x0(i,:));

end

[fmax0,index0]=max(f0) ;

pbest=x0 ; % initial pbest

gbest=x0(index0,:) ; % initial gbest

% pso initialization------------------------------------------------end

% pso algorithm---------------------------------------------------start

ite=1 ;

tolerance=1 ;

while ite>=maxite && tolerance<10^-12

YY=ite>=maxite && tolerance<10^-12 ;

w=wmax-(wmax-wmin)*ite/maxite;% update inertial weight

% pso velocity updates

for i=1:n

for j=1:m

t=v(i,j);

r=rand();

ss=pbest(i,j);

rr=x(i,j);

k=rand();

kk=gbest(1,j);

v(i,j)=w*t+c1*r*(pbest(i,j)-x(i,j))...

+c2*k*(gbest(1,j)-x(i,j));

V=v(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

for i=1:n

f(i,1)=ofun(x(i,:));

end

% updating pbest and fitness

for i=1:n

if f(i,1)>f0(i,1)

pbest(i,:)=x(i,:) ;

f0(i,1)=f(i,1) ;

end

end

[fmax,index]=max(f0) ; % finding out the best particle

ffmax(ite,run)=fmax; % storing best fitness

ffite(run)=ite; % storing iteration count

% updating gbest and best fitness

AA=fmax;

BB=fmax0;

if fmax>fmax0

% CC=pbest(index,:)

gbest=pbest(index,:);

fmax0=fmax;

end

% calculating tolerance

if ite<100;

tolerance=abs(ffmax(ite-100,run)-fmax0) ;

end

% displaying iterative results

if ite==1

disp(sprintf('Iteration Best particle Objective fun'));

end

disp(sprintf('%8g %8g %8.4f',ite,index,fmax0)) ;

ite=ite+1;

end

% pso algorithm-----------------------------------------------------end

gbest ;

fvalue=10*(gbest(1)-1)^2+20*(gbest(2)-2)^2+30*(gbest(3)-3)^2 ;

fff(run)=fvalue;

rgbest(run,:)=gbest ;

disp(sprintf('--------------------------------------'))

end

% pso main program------------------------------------------------------end

% disp(sprintf('\n')) ; %create space or gap

% disp(sprintf('*********************************************************'));

% disp(sprintf('Final Results-----------------------------'));

[bestfun,bestrun]=max(fff)

best_variables=rgbest(bestrun,:)

% disp(sprintf('*********************************************************'));

toc

% PSO convergence characteristic

plot(ffmax(1:ffite(bestrun),bestrun))

xlabel('Iteration')

ylabel('Fitness value')

title('PSO convergence')

could you please help me on this.

[Walter Roberson]

you set tolerance to 1 and then you while tolerance < 1e-12 which would immediately fail .

[jaah navi]

yes.Thanks for your comment.I have changed it.