gusucode.com > 遗传算法 gaot工具箱matlab源码程序 > code_rar/gaot/binaryMutation.m
function [parent] = binaryMutate(parent,bounds,Ops) % Binary mutation changes each of the bits of the parent % based on the probability of mutation % % function [newSol] = binaryMutate(parent,bounds,Ops) % parent - the first parent ( [solution string function value] ) % bounds - the bounds matrix for the solution space % Ops - Options for binaryMutation [gen prob_of_mutation] % Binary and Real-Valued Simulation Evolution for Matlab % Copyright (C) 1996 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. pm=Ops(2); numVar = size(parent,2)-1; % Get the number of variables % Pick a variable to mutate randomly from 1-number of vars rN=rand(1,numVar)<pm; parent=[abs(parent(1:numVar) - rN) parent(numVar+1)];