public IteratedLocalSearch(double[] masks, SingleTrajectoryContinuousSolver local_search, TerminationEvaluationMethod local_search_termination_condition, CreateRandomNeighborhoodMethod generator = null)
{
mLocalSearch = local_search;
mLocalSearchTerminationCondition = local_search_termination_condition;
mMasks = (double[])masks.Clone();
mNeighborSolutionProvider = generator;
if (mNeighborSolutionProvider == null)
{
mNeighborSolutionProvider = (x, index, constraints) =>
{
double[] lower_bounds = null;
double[] upper_bounds = null;
if (mLowerBounds == null || mUpperBounds == null)
{
Tuple <double[], double[]> bounds = null;
if (constraints is Tuple <double[], double[]> )
{
bounds = constraints as Tuple <double[], double[]>;
}
else
{
throw new InvalidCastException();
}
lower_bounds = bounds.Item1;
upper_bounds = bounds.Item2;
}
else
{
lower_bounds = mLowerBounds;
upper_bounds = mUpperBounds;
}
if (lower_bounds.Length < x.Length)
{
throw new ArgumentOutOfRangeException();
}
if (upper_bounds.Length < x.Length)
{
throw new ArgumentOutOfRangeException();
}
double[] x_p = (double[])x.Clone();
for (int i = 0; i < mMasks.Length; ++i)
{
int mindex = (index + i) % x_p.Length;
double new_val = mMasks[i] > 0 ? x[(index + i)] + RandomEngine.Gauss(0, mMasks[i]) : x[(index + i) % x.Length];
new_val = System.Math.Max(lower_bounds[mindex], new_val);
new_val = System.Math.Min(upper_bounds[mindex], new_val);
x_p[mindex] = new_val;
}
return(x_p);
};
}
}
protected virtual double[] MutateStrategy(double[] stddevs)
{
double[] child_stddevs = new double[stddevs.Length];
for (int i = 0; i < stddevs.Length; ++i)
{
child_stddevs[i] = stddevs[i] + RandomEngine.Gauss(0, System.Math.Sqrt(System.Math.Abs(stddevs[i])));
}
return(child_stddevs);
}
public StochasticHillClimber(double[] masks, CreateRandomNeighborhoodMethod generator = null)
{
mMasks = (double[])masks.Clone();
mSolutionGenerator = generator;
if (mSolutionGenerator == null)
{
mSolutionGenerator = (x, index, constraints) =>
{
double[] lower_bounds = null;
double[] upper_bounds = null;
if (mLowerBounds == null || mUpperBounds == null)
{
Tuple <double[], double[]> bounds = null;
if (constraints is Tuple <double[], double[]> )
{
bounds = constraints as Tuple <double[], double[]>;
}
else
{
throw new InvalidCastException();
}
lower_bounds = bounds.Item1;
upper_bounds = bounds.Item2;
}
else
{
lower_bounds = mLowerBounds;
upper_bounds = mUpperBounds;
}
if (lower_bounds.Length < x.Length)
{
throw new ArgumentOutOfRangeException();
}
if (upper_bounds.Length < x.Length)
{
throw new ArgumentOutOfRangeException();
}
double[] x_p = (double[])x.Clone();
for (int i = 0; i < mMasks.Length; ++i)
{
int mindex = (index + i) % x_p.Length;
double new_val = mMasks[i] > 0 ? x[(index + i)] + RandomEngine.Gauss(0, mMasks[i]) : x[(index + i) % x.Length];
new_val = System.Math.Max(lower_bounds[mindex], new_val);
new_val = System.Math.Min(upper_bounds[mindex], new_val);
x_p[mindex] = new_val;
}
return(x_p);
};
}
}
protected virtual double[] MutateStrategy(double[] stddevs)
{
double tau = 1.0 / System.Math.Sqrt(2.0 * stddevs.Length);
double tau_p = 1.0 / System.Math.Sqrt(2.0 * System.Math.Sqrt(stddevs.Length));
double[] child_stddevs = new double[stddevs.Length];
for (int i = 0; i < stddevs.Length; ++i)
{
child_stddevs[i] = stddevs[i] * System.Math.Exp(RandomEngine.Gauss(0, tau_p) + RandomEngine.Gauss(0, tau));
}
return(child_stddevs);
}
protected virtual ContinuousSolution MutateVector(ContinuousSolution solution, double[] lower_bounds, double[] upper_bounds, object constraints)
{
double[] x = new double[mDimension];
double[] strategy = solution.GetMutationStrategy();
for (int i = 0; i < mDimension; ++i)
{
x[i] = solution[i] + RandomEngine.Gauss(0, strategy[i]);
x[i] = System.Math.Max(lower_bounds[i], x[i]);
x[i] = System.Math.Min(upper_bounds[i], x[i]);
}
return(new ContinuousSolution(x, double.MaxValue));
}