|
public static GetTotalDistance ( |
||
| startLocation | ||
| locations | ||
| Результат | double | |
public TravellingSalesmanAlgorithm(Location startLocation, Location[] destinations, int populationCount)
{
if (startLocation == null)
{
throw new ArgumentNullException("startLocation");
}
if (destinations == null)
{
throw new ArgumentNullException("destinations");
}
if (populationCount < 2)
{
throw new ArgumentOutOfRangeException("populationCount");
}
if (populationCount % 2 != 0)
{
throw new ArgumentException("The populationCount parameter must be an even value.", "populationCount");
}
_startLocation = startLocation;
destinations = (Location[])destinations.Clone();
foreach (var destination in destinations)
{
if (destination == null)
{
throw new ArgumentException("The destinations array can't contain null values.", "destinations");
}
}
// This commented method uses a search of the kind "look for the nearest non visited location".
// This is rarely the shortest path, yet it is already a "somewhat good" path.
destinations = _GetFakeShortest(destinations);
_populationWithDistances = new KeyValuePair <Location[], double> [populationCount];
// Create initial population.
for (int solutionIndex = 0; solutionIndex < populationCount; solutionIndex++)
{
var newPossibleDestinations = (Location[])destinations.Clone();
// Try commenting the next 2 lines of code while keeping the _GetFakeShortest active.
// If you avoid the algorithm from running and press reset, you will see that it always
// start with a path that seems "good" but is not the best.
//for(int randomIndex=0; randomIndex<newPossibleDestinations.Length; randomIndex++)
//RandomProvider.FullyRandomizeLocations(newPossibleDestinations);
var distance = Location.GetTotalDistance(startLocation, newPossibleDestinations);
var pair = new KeyValuePair <Location[], double>(newPossibleDestinations, distance);
_populationWithDistances[solutionIndex] = pair;
}
Array.Sort(_populationWithDistances, _sortDelegate);
}
private void generateLines()
{
Location[] bestSolutionSoFar = _bestSolutionSoFar;
Location.GetTotalDistance(_startLocation, bestSolutionSoFar);
_tspSegments.Clear();
if (bestSolutionSoFar.Length > 0)
{
var actualLocation = _startLocation;
int index = 0;
int dropCount = 0;
foreach (var destination in _AddEndLocation(bestSolutionSoFar))
{
var line = new TSPSegment()
{
start = new Vector2(actualLocation.X, actualLocation.Y), end = new Vector2(destination.X, destination.Y)
};
if (line.LineLength() > kJumpThreshold)
{
line.type = TSPSegment.LineType.Jump;
}
else
{
line.type = TSPSegment.LineType.Draw;
}
_tspSegments.Add(line);
actualLocation = destination;
index++;
}
Debug.WriteLine("Total long jumps: " + dropCount);
Debug.WriteLine("Segments added: " + _tspSegments.Count);
}
}
public void Reproduce()
{
var bestSoFar = _populationWithDistances[0];
int halfCount = _populationWithDistances.Length / 2;
for (int i = 0; i < halfCount; i++)
{
var parent = _populationWithDistances[i].Key;
var child1 = _Reproduce(parent);
var child2 = _Reproduce(parent);
var pair1 = new KeyValuePair <Location[], double>(child1, Location.GetTotalDistance(_startLocation, child1));
var pair2 = new KeyValuePair <Location[], double>(child2, Location.GetTotalDistance(_startLocation, child2));
_populationWithDistances[i * 2] = pair1;
_populationWithDistances[i * 2 + 1] = pair2;
}
// We keep the best alive from one generation to the other.
_populationWithDistances[_populationWithDistances.Length - 1] = bestSoFar;
Array.Sort(_populationWithDistances, _sortDelegate);
}
public void MutateDuplicates()
{
bool needToSortAgain = false;
int countDuplicates = 0;
var previous = _populationWithDistances[0];
for (int i = 1; i < _populationWithDistances.Length; i++)
{
var current = _populationWithDistances[i];
if (!previous.Key.SequenceEqual(current.Key))
{
previous = current;
continue;
}
countDuplicates++;
needToSortAgain = true;
RandomProvider.MutateRandomLocations(current.Key);
_populationWithDistances[i] = new KeyValuePair <Location[], double>(current.Key, Location.GetTotalDistance(_startLocation, current.Key));
}
if (needToSortAgain)
{
Array.Sort(_populationWithDistances, _sortDelegate);
}
}