@Override
public Solution execute() {
Solution s = null;
Solution s_;
do {
s_ = factory.newSolution();
localSearch.getProblem().setInitialSolution(s_);
s_ = localSearch.execute();
if (s == null || s_.getCost() < s.getCost()) {
s = s_;
}
// System.out.println(String.format("it:%d, current: %f, best: %s.", current_it,
// s.getCost(), optimizationResult.getBestSolution().getCost()));
} while (endIteration(s_));
return s;
}
@Override
public Solution execute() {
Solution s = initialSolution == null ? problem.getInitialSolution() : initialSolution;
System.out.println("Initial s: " + problem.getCostEvaluator().eval(s));
int i = 0;
int totalIt = 0;
Solution s_;
while (i < maxItWithoutImprovement && totalIt < max_it) {
System.out.println("#### i = " + i + "####");
double lastSCost = s.getCost();
int k = 0;
do {
if (totalIt > max_it) {
break;
}
s_ = neighborhoods[k].getRandomNeighbor(s); // pick at random
localSearchMethod.setProblem(problem);
localSearchMethod.getProblem().setInitialSolution(s_);
s_ = localSearchMethod.execute();
System.out.println("s_, n" + k + ": " + s_.getCost());
if (s_.getCost() < s.getCost()) {
s = s_;
k = 0;
} else {
k++;
}
totalIt++;
} while (endIteration(s_) && k < neighborhoods.length);
if (lastSCost > s.getCost()) {
i = 0;
} else {
i++;
}
}
System.out.println("Final s: " + s.getCost());
return s;
}
