Function problem in loop

Dear researchers i am facing a problem in using function while running in a loop please guide me to solve the problem. My objective is to get the Gbest values over every iteration. Here is the code which i am using and intnded to run in a loop for i=1:10

First function

function out=fns1(X)
x1=X(:,1);
x2=X(:,2);
x3=X(:,3);
x4=X(:,4);
x5=X(:,5);
x6=X(:,6);
x7=X(:,7);
x8=X(:,8);
x9=X(:,9);
x10=X(:,10);
p1=P(:,1);
p2=P(:,2);
p3=P(:,3);
p4=P(:,4);
p5=P(:,5);
p6=P(:,6);
p7=P(:,7);
p8=P(:,8);
p9=P(:,9);
p10=P(:,10);
out = p1.*x1+p2.*x2+p3.*x3+p4.*x4+p5.*x5+p6.*x6+p7.*x7+p8.*x8+p9.*x9+p10.*x10+3;
end

Second Function

function out= fns(X)
x1=X(:,1);
x2=X(:,2);
x3=X(:,3);
x4=X(:,4);
x5=X(:,5);
x6=X(:,6);
x7=X(:,7);
x8=X(:,8);
x9=X(:,9);
x10=X(:,10);
p1=P(:,1);
p2=P(:,2);
p3=P(:,3);
p4=P(:,4);
p5=P(:,5);
p6=P(:,6);
p7=P(:,7);
p8=P(:,8);
p9=P(:,9);
p10=P(:,10);
 fx =p.*x1+p.*x2+p.*x3+p.*x4+p.*x5+p.*x6+p.*x7+p.*x8+p.*x9+p.*x10+3;
for i=1:size(fx,1)
    if fx(i,:)>=0
        fit(i,:)=1./(1+fx(i,:));
    elseif fx(i,:)<0
        fit(i,:)=1+abs(fx(i,:));
    end
end
out=fit;

Here is the main file which call these function

%%%%%
load s1.txt
load s2.txt
load s3.txt
load s4.txt
load s5.txt
load s6.txt
load s7.txt
load s8.txt
load s9.txt
load s10.txt
load p1.txt
load p2.txt
load p3.txt
load p4.txt
load p5.txt
load p6.txt
load p7.txt
load p8.txt
load p9.txt
load p10.txt
s1g=s1(:,1);
s2g=s2(:,1);
s3g=s3(:,1);
s4g=s4(:,1);
s5g=s5(:,1);
s6g=s6(:,1);
s7g=s7(:,1);
s8g=s8(:,1);
s9g=s9(:,1);
s10g=s10(:,1);

p1=p1(:,1);
p2=p2(:,1);
p3=p3(:,1);
p4=p4(:,1);
p5=p5(:,1);
p6=p6(:,1);
p7=p7(:,1);
p8=p8(:,1);
p9=p9(:,1);
p10=p10(:,1);
foodsource=10;
D=10;%%% dimension of the problem
lb=[];
ub=[];
XYZ=[];
fxval=[];
fxind=[];
for i=1:2
lb=[0 0 0 0 0 0 0 0 0 0];%% lower bound
ub=[s1g(i) s2g(i) s3g(i) s4g(i) s5g(i) s6g(i) s7g(i) s8g(i) s9g(i) s10g(i)];%%% upper bound
P=[p1(i) p2(i) p3(i) p4(i) p5(i) p6(i) p7(i) p8(i) p9(i) p10(i)];
N=foodsource;%%%population
limit= (N.*D);%%%used for scout phase
trial=zeros(N,1)%%%init tozero
max_iter=150;
for i=1:N
     for j=1:D
         %A(i,j)=ub(:,j)-lb(:,j)
        A(i,j)= ub(:,j);
     end
     
 end
for i=1:N
       for j=1:D
    pos(i,j)=  ub(:,j);
   end
end

fx(i,:,:) = fns1(pos(i,:,:)); %%% Miniiation objective function

  fx1(i,:,:) = fns(pos(i,:,:)); %%% Max fitness function
 
 for  iter=1:max_iter
 for i=1:N
      Xnew(i,:,:)=pos(i,:);
 Xnew(i,:,:)=pos(i,:,:);
     B=max(A(:,1));
    [M,I] = max(A(:,1));
     p2c= (I*D);
      partner= ceil (rand*N); 
 while (partner==i)
      partner=ceil(rand*N); 
 end

 X=pos(i,p2c);
 Xp=pos(partner,p2c);
Xnew(p2c)= X +0.2.*(X-Xp);
 %%%check the bounds%%%
 for j=1:D
     if Xnew(j)>ub(j)
         Xnew(j)=ub(j);
     elseif Xnew(j)<lb(j)
         Xnew(j)=lb(j);
     end
 end
 
 %%%perform greedy selection
fnew(i,:,:)=fns1(Xnew(i,:,:));
 if fnew(i,:,:) <fx(i,:,:)
  pos(i,:,:)=Xnew(i,:,:);
  fx(i,:,:)=fnew(i,:,:);
  trial(i)=0;
 else
      trial(i)= trial(i)+1;
 end
  end%%% End for loop
 prob=fx./sum(fx);
     for i=1:N   
   if(rand<prob(i)) 
Xnew(i,:,:)=pos(i,:,:);
p2c= (I*D);
         partner=ceil(rand*N);
        while (partner==1)
             partner=ceil(rand*N);
        end
        X=pos(i,p2c);
        Xp=pos(partner,p2c);
Xnew(p2c)= X + 0.2.*(X-Xp);
        %%%%Check the bounds
        for j=1:D
            if Xnew(j)>ub(j)
                Xnew(j)=ub(j);
            elseif Xnew(j)<lb(j)
                Xnew(j)=lb(j);
            end
        end
        %%%perform the greedy selection
fnew(i,:,:)=fns1(Xnew(i,:,:));
        if fnew(i,:,:)<fx(i,:,:)
            pos(i,:,:)=Xnew(i,:,:);
            fx(i,:,:)=fnew(i,:,:);
            trial(i)=0;
        else
            trial(i)=trial(i)+1;
        end
   end
    
 end
 
 %%%memorize the best soln so far
 
 [ fxval, fxind]=min(fx);
 Gbest(i,:,:)=pos(fxind,:);
   XYZ(i,:,:)=Gbest(i,:,:);
  Xbest(iter,:)= Gbest(i,:,:);
  Fbest(iter)=fxval;
  Fbest1(iter)= fns1(Gbest(i,:,:));
  xyz=sum(Gbest(i,:,:));
  %%% Show iter information
 disp(['iteration'  num2str(iter)  ' Best Cost : =' num2str(Fbest(iter))]);

 H=find(trial>limit);
 
 if length (H)>0
     %%% generate population randomly for such H
     for j=1:D
        pos(H,j)=lb(:,j) +rand.*(ub(:,j)-lb (:,j));
 %pos(H,j)=ub(:,j)
     end
     fx(H,:)=fns1(pos(H,:));
 end
  %%%plot the result
 plot(Fbest1, 'r', 'Linewidth',2);
 xlabel=('Iteration');
 ylabel=('Fitness value');
 grid on
 end
end
%%%%

The values for p1-p10 and values of x1-x10 are changing with respect to each time slot. I need to get the Gbest=pos(fxind,:) over every iteration for for the loop i intended to run is for i=1:100.

Thanks in advance

[Daniel Pollard]

https://www.mathworks.com/matlabcentral/answers/6200-tutorial-how-to-ask-a-question-on-answers-and-get-a-fast-answer

Read this whole page, but I point you in particular to point 5, your code is impossible to read.

[KSSV]

Saving every column of a amtrix into an array is meaning less.

[Amin Waqas]

Thanks Daniel Pollard i will take care your suggestions in future

[Amin Waqas]

KSSV what you suggest to change plz Highlight so that i can get my answer

Answer 1

[KSSV]

function out=fns1(X)
x1=X(:,1);
x2=X(:,2);
x3=X(:,3);
x4=X(:,4);
x5=X(:,5);
x6=X(:,6);
x7=X(:,7);
x8=X(:,8);
x9=X(:,9);
x10=X(:,10);
p1=P(:,1);
p2=P(:,2);
p3=P(:,3);
p4=P(:,4);
p5=P(:,5);
p6=P(:,6);
p7=P(:,7);
p8=P(:,8);
p9=P(:,9);
p10=P(:,10);
out = p1.*x1+p2.*x2+p3.*x3+p4.*x4+p5.*x5+p6.*x6+p7.*x7+p8.*x8+p9.*x9+p10.*x10+3;
end

The above function can be simply replaced with the line:

out = sum(X.*P,2)+3 ;

[Amin Waqas]

By doing this i am getting the following error

Undefined function or variable 'P'.

Error in fns1 (line 15)

p1=P(:,1);

Error in Try1 (line 108)

fx(i,:,:) = fns1(pos(i,:,:)); %%% Miniiation objective function

[KSSV]

Obviosuly, in the function you are not taking P as input....

[Amin Waqas]

by taking P as input as out=fns1(X,P) Still error the same

[KSSV]

You have to show the whole code which you have tried and lead to error.

[Amin Waqas]

KSSV sir attched find the code files