tsp_crossover_permutation.m

tsp（旅行商问题） 利用matlab遗传算法、模拟退火算法以及lingo动态规划求解

function xoverKids  = tsp_crossover_permutation(parents,options,NVARS, ...
    FitnessFcn,thisScore,thisPopulation)
nKids = length(parents)/2;
xoverKids = cell(nKids,1); % Normally zeros(nKids,NVARS);
index = 1;

for i=1:nKids
    % here is where the special knowledge that the population is a cell
    % array is used. Normally, this would be thisPopulation(parents(index),:);
    parent = thisPopulation{parents(index)};
    index = index + 2;

    % Flip a section of parent1.
    p1 = ceil((length(parent) -1) * rand);
    p2 = p1 + ceil((length(parent) - p1- 1) * rand);
    child = parent;
    child(p1:p2) = fliplr(child(p1:p2));
    xoverKids{i} = child; % Normally, xoverKids(i,:);
end