function [parent] = multiNonUnifMutation(parent,bounds,Ops)% Multi-Non uniform mutation changes all 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 multiNonUnifMutation %          [gen #MultiNonUnifMutations 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 Generationmg=Ops(3); 				% Maximum Number of Generationsb=Ops(4);                               % Shape parameterdf = bounds(:,2) - bounds(:,1); 	% Range of the variablesnumVar = size(parent,2)-1; 		% Get the number of variables% Now mutate that pointmd = round(rand(1,numVar));for i = 1:numVar  if md(i)    parent(i)=parent(i)+delta(cg,mg,bounds(i,2)-parent(i),b);  else    parent(i)=parent(i)-delta(cg,mg,parent(i)-bounds(i,1),b);  endend