www.gusucode.com > 遗传算法 gaot工具箱matlab源码程序 > code_rar/gaot/nonUnifMutation.m
function [parent] = nonUnifMutate(parent,bounds,Ops) % Non uniform mutation changes one of the parameters of the parent % based on a non-uniform probability distribution. This Gaussian % distribution starts wide, and narrows to a point distribution as the % current generation approaches the maximum generation. % % function [newSol] = multiNonUnifMutate(parent,bounds,Ops) % parent - the first parent ( [solution string function value] ) % bounds - the bounds matrix for the solution space % Ops - Options for nonUnifMutate[gen #NonUnifMutations maxGen b] % 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. cg=Ops(1); % Current Generation mg=Ops(3); % Maximum Number of Generations b=Ops(4); % Shape parameter df = bounds(:,2) - bounds(:,1); % Range of the variables numVar = size(parent,2)-1; % Get the number of variables % Pick a variable to mutate randomly from 1 to number of vars mPoint = round(rand * (numVar-1)) + 1; md = round(rand); % Choose a direction of mutation if md % Mutate towards upper bound newValue=parent(mPoint)+delta(cg,mg,bounds(mPoint,2)-parent(mPoint),b); else % Mutate towards lower bound newValue=parent(mPoint)-delta(cg,mg,parent(mPoint)-bounds(mPoint,1),b); end parent(mPoint) = newValue; % Make the child