function [ch1,ch2] = partmapXover(par1,par2,bounds,Ops)% Partmap crossover takes two parents P1,P2 and performs a partially% mapped crossover.  %% function [c1,c2] = partmapXover(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;pos1 = round(rand*sz + 0.5);pos2 = round(rand*sz + 0.5);while pos2 == pos1   pos2 = round(rand*sz + 0.5);endif pos1 > pos2   t = pos1; pos1 = pos2; pos2 = t;end    ss1 = par1(pos1:pos2); ss2 = par2(pos1:pos2);ch1 = par2; ch2 = par1;for i = [1:pos1-1 pos2+1:sz]   ch1(i) = par1(i);   j = find(ch1(i) == ss2);   while ~isempty(j)      ch1(i) = ss1(j);      j = find(ch1(i) == ss2);   end   ch2(i) = par2(i);   j = find(ch2(i) == ss1);   while ~isempty(j)      ch2(i) = ss2(j);      j = find(ch2(i) == ss1);   endend