??? undefined function or method 'ga14bus_29_sep_2018' for input arguments of type 'double'.

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tahseen alshmary
tahseen alshmary on 30 Sep 2018
Commented: Walter Roberson on 30 Sep 2018
??? undefined function or method 'ga14bus_29_sep_2018' for input arguments of type 'double'.
dear sirs how can i solve this problem in matlab 2009b
  1 Comment
Walter Roberson
Walter Roberson on 30 Sep 2018
Note: you marked the question has having to do with Extended Symbolic Math Toolbox, which was a toolbox that was no longer available in the MATLAB release you indicate you are using, R2009b.
You do not appear to be using any function from the Extended Symbolic Math Toolbox: generally speaking those would show up as calls to maple() or evalin(symengine) or feval(symengine)

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Answers (1)

tahseen alshmary
tahseen alshmary on 30 Sep 2018
Edited: Walter Roberson on 30 Sep 2018
clf
clc
clear
close all
mr_max =10;
miscoord =[];
dt_run =[];
fitrecrun =[];
f1bestrecrun =[];
f2bestrecrun =[];
f3bestrecrun =[];
mr_bestever =inf;
good_dt =0;
good_ub =0;
good_lb =0;
good_dt_lb_ub =0;
TMbestrec =[];
for mr =1:mr_max
end
    %A setup the GA
     ff ='ga14bus'; %objective function 
    npar  =42;  % number of optimazation variables
    varhi =1.0; % varible limit 
    varlo =0.01;% varible limit 
    %_____________________________________________________________________
      % B stopping criteria 
      maxit = 1500;            % max number of iteration 
      mincost =-9999999;       % minimum cost 
      %______________________________________________________________________
      % C GA parameter 
      popsize = 100;                   % set population size 
      mutrate = 0.02;                  % set mutation rate
      selection = 0.5;                 % fraction of population kept
      Nt  = npar;                      % continuous parameter GA Nt=#variables
      keep = floor(selection*popsize); % # population members that survive 
      nmut = ceil((popsize-1)*Nt*mutrate); %total number of mutations
      M  = ceil((popsize-keep)/2);      % number of mating 
     %______________________________________________________________________
     % Creat the intial population
     iga    = 0;                      % generation counter
     par    = (varhi-varlo)*rand(popsize,npar)+varlo;  % random
     % make the variable discrete before evaluation 
     temp_par    = size(par);
     row_par     = temp_par(1);
     col_par     = temp_par(2);
     for i= 1:row_par
           for j = 1:col_par
             if mod(par(i,j),0.01)<1e-10
                 par(i,j)   =par(i,j);
             else
                 par(i,j) =(ceil(par(i,j))/0.01)*0.01;
             end
           end
     end
     cost     = ga14bus_29_Sep_2018(par);    % calculates population cost using objective function
     [cost,ind] = sort(cost);            % min cost in element 1
     par        = par(ind,:);            % sort continuous 
     minc(1)    = min(cost);             % minc contains min of population cost 
     meanc(1) = mean(cost);              % meanc contains mean of population cost
     fitrec   = [];
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