/// <summary>
/// Generates a random neighbour and applies it to the current state
/// </summary>
/// <returns>The neighbour that was applied</returns>
public Neighbour <S> ApplyRandomNeighbour()
{
Neighbour <S> neighbour = GetRandomNeighbour();
ApplyNeighbour(neighbour);
return(neighbour);
}
/// <summary>
/// Starts searching for an optimal solution
/// </summary>
/// <param name="initialState">The start state from where to search</param>
/// <param name="bestStateSoFar">Reference where the result (and updates) are supposed to be stored</param>
public void Search(S initialState, ref string bestStateSoFar)
{
S state = initialState;
double bestTotalScore = initialState.Score;
double previousScore = bestTotalScore;
double temperature = StartTemperature;
int iterations = 0;
while (MaxTimeAllowed > Timer.Elapsed.TotalSeconds)
{
iterations++;
// Get a random neighbour and apply it
Neighbour <D> neighbour = state.GetRandomNeighbour();
state.ApplyNeighbour(neighbour);
double newScore = state.Score;
// Update the scores and best solution if necessary
if (newScore <= previousScore)
{
if (newScore < bestTotalScore)
{
bestStateSoFar = state.Data.ToString();
bestTotalScore = newScore;
}
previousScore = newScore;
}
else
{
// There is a chance the neighbour is reverted
double chance = Math.Exp((previousScore - newScore) / temperature);
double random = Random.NextDouble();
if (random > chance)
{
state.RevertNeighbour(neighbour);
}
else
{
previousScore = newScore;
}
}
// Reset the temperature if the threshold has been reached
if (temperature < ResetTemperatureThreshold)
{
temperature = StartTemperature;
}
// Multiply the temperature if needed
if (iterations % MultiplyTemperaturePerIterations == 0)
{
temperature *= TemperatureMultiplier;
}
}
}
public Neighbour <RecursiveTree <Node> > GetRandomNeighbour(RecursiveTree <Node> data)
{
List <Neighbour <RecursiveTree <Node> > > neighbourlist = new List <Neighbour <RecursiveTree <Node> > >();
// Create a random MoveUpNeighbour
Neighbour <RecursiveTree <Node> > move = MoveUpNeighbourSpace.GetRandomNeighbour(data);
neighbourlist.Add(move);
// Generate Splits amount of random SplitNeighbours
for (int i = 0; i < Splits; i++)
{
Neighbour <RecursiveTree <Node> > split = SplitNeighbourSpace.GetRandomNeighbour(data);
neighbourlist.Add(split);
}
// Return the list with the single Move and multiple SplitNeighbours
return(new MultipleNeighbourNeighbour <RecursiveTree <Node> >(neighbourlist));
}
/// <summary>
/// Reverts a neighbour
/// </summary>
/// <param name="neighbour">The neighbour to revert</param>
public virtual void RevertNeighbour(Neighbour <S> neighbour)
{
neighbour.Revert();
//Score -= neighbour.Delta(); // TODO: use the delta again
}
/// <summary>
/// Applies a neighbour
/// </summary>
/// <param name="neighbour">The neigbour to apply</param>
public virtual void ApplyNeighbour(Neighbour <S> neighbour)
{
neighbour.Apply();
//Score += neighbour.Delta(); // TODO: use the delta again
}
