function [ch1,ch2,t] = uniformxover(par1,par2,bounds,Ops)% Uniform crossover takes two parents P1,P2 and performs uniform% crossover on a permuation string.  %% function [c1,c2] = linearOrderXover(p1,p2,bounds,Ops)% p1      - the first parent ( [solution string function value] )% p2      - the second parent ( [solution string function value] )% bounds  - the bounds matrix for the solution space% Ops     - Options matrix for simple crossover [gen #SimpXovers].% 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.sz = size(par1,2)-1;ch1 = par1;ch2 = par2;t = round(rand(1,sz));szt = sum(t);idx = 1:sz;idxt = idx(logical(t));plst = idxt;for i = 1:szt   plst(i) = find(par2 == par1(idxt(i)));endplst = sort(plst);for i = 1:szt   ch1(idxt(i)) = par2(plst(i));endszt = sz - szt;idxt = idx(~t);plst = idxt;for i = 1:szt   plst(i) = find(par1 == par2(idxt(i)));endplst = sort(plst);for i = 1:szt   ch2(idxt(i)) = par1(plst(i));end