public Tabu(LocationMap map)
{
this.map = map; // use the provided LocationMap for TSP
tabuListSize = (int)Math.Sqrt(map.PointCollection.Count) + 2; // heuristic for a good list size
// assume LocationMap can choose whether to loop the last point in the path back to the first point
path = new int[map.PointCollection.Count];
for (int i = 0; i < path.Length; i++)
{
path[i] = i;
}
bestPath = path.ToArray();
tabuList = new int[map.PointCollection.Count, map.PointCollection.Count];
for (int i = 0; i < map.PointCollection.Count; i++)
{
for (int j = 0; j < map.PointCollection.Count; j++)
{
tabuList[i, j] = 0;
}
}
currentDistance = map.CalcRouteDistance(path);
bestDistance = currentDistance;
}
public void SearchOneIteration()
{
if (path.Length < 2)
{
return; // don't even bother
}
// use the first neighbor swap to begin with
int bestI = -1;
int bestJ = -1;
double currentBestDistance = double.MaxValue;
// first search the neighborhood of potential swaps
Dictionary <Tuple <int, int>, int[]> neighborhoodList = new Dictionary <Tuple <int, int>, int[]>();
for (int i = 0; i < path.Length; i++)
{
for (int j = i + 1; j < path.Length; j++)
{
int[] newPath = path.ToArray(); // need a deep copy
SwapIndex(newPath, i, j);
double thisDistance = map.CalcRouteDistance(newPath);
if ((tabuList[i, j] <= 0 && thisDistance < currentBestDistance) ||
(thisDistance < bestDistance)) // less than global best aspiration criteria
{
bestI = i;
bestJ = j;
currentBestDistance = thisDistance;
if (thisDistance < bestDistance)
{
bestDistance = thisDistance;
bestPath = newPath.ToArray(); // make a copy of the global best solution
}
}
// decrement the tabu list while we are at it
if (tabuList[i, j] > 0)
{
tabuList[i, j]--;
}
}
}
// switch to the selected neighbor and then update the tabu list
if (bestI != -1 && bestJ != -1)
{
SwapIndex(path, bestI, bestJ);
tabuList[bestI, bestJ] = tabuListSize;
}
}