@Override
public void offerSolution() {
FitInstance<Instance> solution = task.getFitInstance(stats.getBestInstance());
System.out.println("Offering solution with f = " + solution.getFitness());
otherAlgorithms
.get(ThreadLocalRandom.current().nextInt(otherAlgorithms.size()))
.acceptSolution(solution);
}
protected Edge addChildToBest(Instance instance) {
List<MutatedInstanceMetaData<Instance, MutationType>> offspring =
crossover.apply(stats.getBestInstance(), instance);
FitInstance<Instance> md0 = task.getFitInstance(offspring.get(0).getInstance());
FitInstance<Instance> md1 = task.getFitInstance(offspring.get(1).getInstance());
if (md0.getFitness() > md1.getFitness()) {
return graph.addNode(
stats.getBestNode(),
offspring.get(0).getMutations(),
md0,
task.getNumberOfFitnessEvaluations());
}
return graph.addNode(
stats.getBestNode(),
offspring.get(1).getMutations(),
md1,
task.getNumberOfFitnessEvaluations());
}
@Override
protected List<Node<Instance>> getStartNodes() {
List<Node<Instance>> startNodes = super.getStartNodes();
if (!offeredSolutions.isEmpty()) {
startNodes.remove(0);
FitInstance<Instance> bestOfferedSolution = Collections.max(offeredSolutions);
offeredSolutions.clear();
Node<Instance> node = addChildToBest(bestOfferedSolution.getInstance()).getDest();
System.out.println(
"Crossover ("
+ stats.getBestFitness()
+ ", "
+ bestOfferedSolution.getFitness()
+ ") best child fitness = "
+ node.getFitness());
startNodes.add(node);
}
return startNodes;
}
