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

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   = [];