📄 unifmutation.m
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function [parent] = uniformMutate(parent,bounds,Ops)
% Uniform mutation changes one of the parameters of the parent
% based on a uniform probability distribution.
%
% 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 uniformMutation [gen #UnifMutations]
% 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.
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-number of vars
mPoint = round(rand * (numVar-1)) + 1;
newValue = bounds(1)+round(rand * df); % Now mutate that point,liu changed
parent(mPoint) = newValue; % Make the child
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