public static TabuAlgorithmResult GenerateResult(int size)
{
var init = new TabuAlgorithmResult()
{
Path = Enumerable.Range(0, size).ToList()
};
init.Shuffle();
return(init);
}
public void Invoke()
{
var init = TabuAlgorithmResult.GenerateResult(_graph.NumberOfCities);
init.CalculateWeight(_graph);
var result = TabuSearch(init);
Result = new AlgorithmResult {
Path = result.Path, Weight = result.Weight
};
}
public TabuAlgorithmResult TabuSearch(TabuAlgorithmResult initialSolution)
{
bestSolution = initialSolution;
TabuAlgorithmResult currentSolution = initialSolution;
_tabuList = new Queue <Move>();
int critCounter = 0;
int currentIteration = 0;
while (!_stopCondition.mustStop(++currentIteration))
{
//algorytm najblizszego sasiada
TabuAlgorithmResult bestNeighborFound =
FindBestNeighbor(currentSolution, _tabuList.ToList(), out var move);
if (bestNeighborFound.Weight < bestSolution.Weight)
{
bestSolution = bestNeighborFound;
critCounter = 0;
}
else
{
//dywersyfikacja
critCounter++;
if (critCounter == _maxCritCounter && _maxCritCounter != 0)
{
currentSolution = TabuAlgorithmResult.GenerateResult(_graph.NumberOfCities);
critCounter = 0;
}
}
//dodawanie ostatniego ruchu
_tabuList.Enqueue(move);
currentSolution = bestNeighborFound;
//max tabu size
if (_tabuList.Count > _maxTabuSize)
{
_tabuList.Dequeue();
}
}
return(bestSolution);
}
public TabuAlgorithmResult FindBestNeighbor(TabuAlgorithmResult currentSolution, List <Move> tabuMoves,
out Move move)
{
int bestCost = Int32.MaxValue;
move = new Move(0, 0);
TabuAlgorithmResult bestResult = new TabuAlgorithmResult();
for (int i = 0; i < currentSolution.Path.Count; i++)
{
for (int j = 1; j < currentSolution.Path.Count; j++)
{
var pathList = new List <int>(currentSolution.Path);
if (j != i)
{
var currMove = new Move(i, j);
TabuAlgorithmResult temp = new TabuAlgorithmResult();
temp.Path = Swap(i, j, pathList);
int currCost = temp.CalculateWeight(_graph);
if (!tabuMoves.Contains(currMove))
{
if (currCost < bestCost || currCost < bestSolution.Weight)
{
bestCost = currCost;
move = new Move(currMove);
bestResult = new TabuAlgorithmResult(temp);
}
}
}
}
}
return(bestResult);
}
public TabuAlgorithmResult(TabuAlgorithmResult alg)
{
Path = new List <int>(alg.Path);
Weight = alg.Weight;
}
