osimplepointxover.sci

站长您好！GATS是一种遗传算法工具箱

function [c1,c2]= OSimplePointXover(p1,p2,bounds,Ops)
// function [c1,c2] = singlePtXover(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].

rng         = (bounds(:,2)-bounds(:,1))';         // The variable ranges'
numArranges     = rng + 1; 		          // Number of each arrages
cumArranges = cumsum([0 numArranges]);
xZomeLength = sum(numArranges)+1; 		  // Length of string is numVar + fit
c1=p1;
c2=p2;
for i= 1:size(numArranges,2)
    sz=numArranges(i);
    pfrom=(cumArranges(i)+1);
    pto=cumArranges(i+1);
    cut = round(rand(1)*(sz-1)+0.5);                 // Generate random cut point U(1,n-1)
    part1 = p1(pfrom:pto);
    part2 = p2(pfrom:pto);
    pm1=part1;
    pm2=part2;
    for i=pfrom:pfrom+cut-1
      pm1(find(pm1=p2(i)))=-1;
      pm2(find(pm2=p1(i)))=-1;
    end
    c1((cut+pfrom):pto)=p2(pfrom+find(pm2>0)-1);
    c2((cut+pfrom):pto)=p1(pfrom+find(pm1>0)-1);

end