GA implementation in matlab without using the toolbox

This is my code for implementing ga in matlab:

% Program for Genetic algorithm to minimize the constrained function ga_test
clear all;
clc;

function f = ga_test(x)

f = 120*x1 + 120*x2 + 120*x3 + 120*x4 + 120*x5 + 120*x6 + 120*x7 + 120*x8 + 120*x9 + 120*x10 + 40*y1 + 40*y2 + 40*y3 + 40*y4 + 40*y5 + 40*y6 + 40*y7 + 40*y8 + 40*y9 + 40*y10+ 40*y11 + 40*y12 + 40*y13 + 40*y14 + 40*y15 + 40*y16 + 40*y17 + 40*y18 + 40*y19+ 40*y20;

% Setup the Genetic Algorithm

fitnessfunction= @ga_test;

N = 1310;  % number of optimization (decision) variables

popsize = 8 ; % set population size = number of chromosomes

max_iteration = 50;  % max number of iterations

minimum_cost = 120;  % minimum cost

mutation_rate = 0.01; % mutation rate

selection_rate = 0.5; % selection rate: fraction of population 

nbits = 1;

Nt = nbits*N; % total number of bits in a chormosome

number_mutations = mutation_rate*N*(popsize-1); % number of mutations

% #population members that survive (Nkeep = Xrate*Npop); Nkeep survive for mating, and (Npop - Nkeep) are discarded to make room for the new offspring

keep = floor(selection_rate*popsize); 

iga=0; % generation counter initialized

pop=round(rand(popsize,Nt)); % random population of 1s and 0s

cost=feval(fitnessfunction,pop); % calculates population cost using fitnessfunction

[cost,ind]=sort(cost); % min cost in element 1

pop=pop(ind,:); % sorts population with lowest cost first

minc(1)=min(cost); % minc contains min of population

while iga < max_iteration  %Iterate through generations

iga=iga+1; % increments generation counter

% Pair and mate

M=ceil((M-keep)/2); % number of matings weights chromosomes based upon position in list probability distribution function

prob=flipud([1:keep]'/sum([1:keep])); 

odds=[0 cumsum(prob(1:keep))]; 

pick1=rand(1,popsize); % mate #1

pick2=rand(1,popsize); % mate #2

% parents contain the indicies of the chromosomes that will mate

ic=1;

while ic<=M

for id=2:keep+1

if pick1(ic)<=odds(id) & pick1(ic)>odds(id-1)

ma(ic)=id-1;

end % if

if pick2(ic)<=odds(id) & pick2(ic)>odds(id-1)

pa(ic)=id-1;

end % if

end % id

ic=ic+1;

end % while

%_______________________________________________________

% Performs mating using single point crossover

ix=1:2:keep; % index of mate #1

xp=ceil(rand(1,M)*(Nt-1)); % crossover point

pop(keep+ix,:)=[pop(ma,1:xp) pop(pa,xp+1:Nt)];

% first offspring

pop(keep+ix+1,:)=[pop(pa,1:xp) pop(ma,xp+1:Nt)];

% second offspring

%_______________________________________________________

% Mutate the population

number_mutations=ceil((popsize-1)*Nt*mutation_rate); % total number of mutations

mrow=ceil(rand(1,number_mutations)*(popsize-1))+1; % row to mutate

mcol=ceil(rand(1,number_mutations)*Nt); % column to mutate

for ii=1:number_mutations

pop(mrow(ii),mcol(ii))=abs(pop(mrow(ii),mcol(ii))-1);

end 

%_______________________________________________________

% The population is re-evaluated for cost decode

cost(2:popsize)=feval(fitnessfunction,pop(2:popsize,:));

%_______________________________________________________

% Sort the costs and associated parameters

[cost,ind]=sort(cost);

pop=pop(ind,:);

%_______________________________________________________

% Stopping criteria

if iga>maxit | cost(1)<mincost

break

end

[iga cost(1)]

end

I still didn't run my code because I do't know how shall I write my objective function and the constraints?? And upon what shall I decide the popsize?

Any help will be highly appreciated.

Answer 1

[gurleen Sohi]

hi..actuallly i need matlab code for the design of IIR filter i.e to find magnitude and group delay of low pass butterworth filter using genetic algorithm....thanks..reply me on my email [e-mail]

[Walter Roberson]

Please start a new question for that topic.

Answer 2

[Navneet kaur]

have you come to know how to remove this error?? @yasmine

[Walter Roberson]

Your objective function should be whatever you want minimized. It will take a vector of input values and must output a scalar score, lower is more "fit".

Answer 3

[Awais khan]

%problem is to maximize x^2 in 0 and 16 range
%%popsize=5
popsize=6;
POP=round(rand(popsize,4))

%%evaluation of the fitness funcs.
for iteration=1:1000
    for ii=1:popsize
        f(ii)=(bin2dec(num2str(POP(ii, :))))^2;
    end

      for ii=1:popsize
          contribution(ii)=f(ii)/sum(f);
      end
      contribution;
      contribution=contribution* popsize
      contribution=round( contribution)
      %pause
      if sum(contribution)>popsize
          [mymax,myindex]=max( contribution)
          contribution(myindex)= contribution(myindex)-1
          if sum(contribution)>popsize
              [mymax,myindex]=max( contribution)
              contribution(myindex)= contribution(myindex)-1
          end
          %pause
      end
      if sum(contribution)<popsize
          [mymax,myindex]=max( contribution)
          contribution(myindex)= contribution(myindex)+1
          if sum(contribution)<popsize
              [mymax,myindex]=max( contribution)
              contribution(myindex)= contribution(myindex)+1
          end
          %pause
      end%%BURAYI DUZELTELIM
      %myindexes=contribution

      %%Elements to be crossovered
      POP
      pause
      m=1;
      for ii=1:popsize
          if contribution(ii)>0
              gett=contribution(ii);
              for jj=1:gett
                  TOCR(m,:)=POP(gett,:);
                  m=m+1;
              end
          end
      end
      myrandperms=randperm(popsize);
      TOCR
      111
      pause
      TOCR=TOCR(myrandperms,:)
     % pause
      CR=0.7;
      %%CROSSOVER %let crossover point be 2
      for ii=1:2:popsize-1
          myrand=rand;
          if myrand<CR

              temp1=TOCR(ii,3:4);
              temp2=TOCR(ii+1,3:4);
              TOCR(ii,3:4)=temp2;
              TOCR(ii+1,3:4)=temp1;

          end
      end
      PM=0.1;
      %%MUTATION
      for ii=1:popsize
          for jj=1:4%%number of bits
              myrand=rand;
              if myrand<PM
                  TOCR(ii,jj)=TOCR(ii,jj)+1;
                  TOCR(ii,jj)=rem(TOCR(ii,jj),2) ;
              end
          end
      end
      POP=TOCR;
  end
  POP

I have some errors in this code and cannot fix, How can i fix these errors to run my code