heuristi.m

基本遗传算法的Matlab工具包

function [c1,c2] = heuristicXover(p1,p2,bounds,Ops)
% Heuristic crossover takes two parents P1,P2 and performs an extrapolation
% along the line formed by the two parents outward in the direction of the
% better parent.
%
% function [c1,c2] = heuristicXover(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 for heuristic crossover, [gen #heurXovers number_of_retries]
retry=Ops(3); 				% Number of retries
i=0;
good=0;
b1=bounds(:,1)';
b2=bounds(:,2)';
numVar = size(p1,2)-1;
% Determine the best and worst parent
if(p1(numVar+1) > p2(numVar+1))
  bt = p1; 
  wt = p2;
else
  bt = p2;
  wt = p1;
end
while i<retry
  % Pick a random mix amount
  a = rand;
  % Create the child
  c1 = a * (bt - wt) + bt;
  % Check to see if child is within bounds
  if (c1(1:numVar) <= b2 & (c1(1:numVar) >= b1))
    i = retry;
    good=1;
  else
    i = i + 1;
  end
end
% If new child is not feasible just return the new children
if(~good) 
  c1 = wt;
end
% Crossover functions return two children therefore return the best
% and the new child created
c2 = bt;
end