function [c1,c2] = simpleXover(p1,p2,bounds,Ops)% Simple crossover takes two parents P1,P2 and performs simple single point% crossover.  %% function [c1,c2] = simpleXover(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.numVar = size(p1,2)-1; 			% Get the number of variables % Pick a cut point randomly from 1-number of varscPoint = round(rand * (numVar-2)) + 1;c1 = [p1(1:cPoint) p2(cPoint+1:numVar+1)]; % Create the childrenc2 = [p2(1:cPoint) p1(cPoint+1:numVar+1)];end