function [c1,c2]= oox(p1,p2,bounds,Ops)% Orderbased crossover takes two parents P1,P2 and performs  order% based crossover by Davis.  %% function [c1,c2] = orderbasedXover(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(p1,2)-1;n=floor(sz/2);cut1 = round(rand*(n-1)+0.5); %Generate random cut point U(1,n/2);cut2 = round(rand*(sz-cut1-1)+1+cut1); %Generate random cut point U(cut1+1,n-1);pm1=p1(1:end-1);pm2=p2(1:end-1);c1=p1;c2=p2;for i=[1:cut1 (cut2+1):sz]  pm1=strrep(pm1,p2(i),-1);  pm2=strrep(pm2,p1(i),-1);endc1((cut1+1):cut2)=p2(find(pm2>0));c2((cut1+1):cut2)=p1(find(pm1>0));