www.gusucode.com > 遗传算法 gaot工具箱matlab源码程序 > code_rar/gaot/initializega.m
function [pop] = initializega(num, bounds, evalFN,evalOps,options) % function [pop]=initializega(populationSize, variableBounds,evalFN, % evalOps,options) % initializega creates a matrix of random numbers with % a number of rows equal to the populationSize and a number % columns equal to the number of rows in bounds plus 1 for % the f(x) value which is found by applying the evalFN. % This is used by the ga to create the population if it % is not supplied. % % pop - the initial, evaluated, random population % populatoinSize - 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] % Binary and Real-Valued Simulation Evolution for Matlab GAOT V2 % Copyright (C) 1998 C.R. Houck, J.A. Joines, M.G. Kay % % C.R. Houck, J.Joines, and M.Kay. A genetic algorithm for function % optimization: A Matlab implementation. ACM Transactions on Mathmatical % Software, Submitted 1996. % % This program is free software; you can redistribute it and/or modify % it under the terms of the GNU General Public License as published by % the Free Software Foundation; either version 1, or (at your option) % any later version. % % This program is distributed in the hope that it will be useful, % but WITHOUT ANY WARRANTY; without even the implied warranty of % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the % GNU General Public License for more details. A copy of the GNU % General Public License can be obtained from the % Free Software Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA. if nargin<5 options=[1e-6 1]; end if nargin<4 evalOps=[]; end if any(evalFN<48) %Not a .m file if options(2)==1 %Float GA estr=['x=pop(i,1); pop(i,xZomeLength)=', evalFN ';']; else %Binary GA estr=['x=b2f(pop(i,:),bounds,bits); pop(i,xZomeLength)=', evalFN ';']; end else %A .m file if options(2)==1 %Float GA estr=['[ pop(i,:) pop(i,xZomeLength)]=' evalFN '(pop(i,:),[0 evalOps]);']; else %Binary GA estr=['x=b2f(pop(i,:),bounds,bits);[x v]=' evalFN ... '(x,[0 evalOps]); pop(i,:)=[f2b(x,bounds,bits) v];']; end end numVars = size(bounds,1); %Number of variables rng = (bounds(:,2)-bounds(:,1))'; %The variable ranges' if options(2)==1 %Float GA xZomeLength = numVars+1; %Length of string is numVar + fit pop = zeros(num,xZomeLength); %Allocate the new population pop(:,1:numVars)=(ones(num,1)*rng).*(rand(num,numVars))+... (ones(num,1)*bounds(:,1)'); else %Binary GA bits=calcbits(bounds,options(1)); xZomeLength = sum(bits)+1; %Length of string is numVar + fit pop = round(rand(num,sum(bits)+1)); end for i=1:num eval(estr); end