initpop.m

人工免疫算法基于遗传MATLAB代码很有用哦

function [pop] = initpop(num,bounds,evalFN)

% pop            - the initial, evaluated, random population 
% num            - the size of the population, i.e. the number to create
% variableBounds - a matrix which contains the bounds of each variable, i.e.
%                  [var1_high var1_low; var2_high var2_low; ....]
% evalFN         - the evaluation fn, usually the name of the .m file for 
%                  evaluation
% evalOps        - any options to be passed to the eval function defaults []
% options        - options to the initialize function, ie. 
%                  [type prec] where eps is the epsilon value 
%                  and the second option is 1 for float and 0 for binary, 
%                  prec is the precision of the variables defaults [1e-6 1]

% SGA_selection Begin
%num=10;
%bounds=[0 9];
%evalFN='gademo1eval';
%a=nargin;
%% check input & error protect

opts=[1e-6 1];

%   Let's create a random starting popluation of size

if any(evalFN<48) %Not a .m file
  %Binary GA
    estr=['x=b2f(pop(i,:),bounds,bits); pop(i,xZomeLength)=', evalFN ';']; 
else %A .m file
  %Binary GA
    estr=['x=b2f(pop(i,:),bounds,bits);[x v]=' evalFN ...
	'(x,[ ]); pop(i,:)=[f2b(x,bounds,bits) v];'];
end

 %Binary GA
  bits=ceil(log2((bounds(:,2)-bounds(:,1))' ./ opts(1)));
  xZomeLength = sum(bits)+1; 		%Length of string is numVar + fit
  pop = round(rand(num,sum(bits)+1));


for i=1:num
  eval(estr);
end