public IEnumerable <double[]> Solve(Term objective, IEnumerable <Term> constraints, Variable[] variables, double[] startPoint)
{
var constraintSquares = constraints.Select(c => TermBuilder.Power(c, 2));
var penalizedObjective = objective + penaltyWeight * TermUtils.SafeSum(constraintSquares);
var compiledPenalizedObjective = penalizedObjective.Compile(variables);
var solution = unconstrainedOptimizer.Solve(x => compiledPenalizedObjective.Differentiate(x), startPoint, gradientNormThreshold);
yield return(solution);
}
protected double[] InitialPoint(List <CNSAT.Var> constraints, RpropResult res)
{
Tuple <double[], double> tup;
bool found = true;
res.initialValue = new double[dim];
res.finalValue = new double[dim];
double[] gradient;
do
{
gradient = new double[dim];
found = true;
res.initialUtil = 1;
for (int i = 0; i < dim; i++)
{
res.initialValue[i] = rand.NextDouble() * ranges[i] + limits[i, 0];
}
this.fevalsCount++;
for (int i = 0; i < constraints.Count; i++)
{
if (constraints[i].Assignment == CNSAT.Assignment.True)
{
if (constraints[i].PositiveTerm == null)
{
constraints[i].PositiveTerm = TermUtils.Compile(constraints[i].Term, this.currentArgs);
}
constraints[i].CurTerm = constraints[i].PositiveTerm;
}
else
{
if (constraints[i].NegativeTerm == null)
{
constraints[i].NegativeTerm = TermUtils.Compile(constraints[i].Term.Negate(), this.currentArgs);
}
constraints[i].CurTerm = constraints[i].NegativeTerm;
}
tup = constraints[i].CurTerm.Differentiate(res.initialValue);
for (int j = 0; j < dim; j++)
{
if (Double.IsNaN(tup.Item1[j]))
{
found = false;
break;
}
gradient[j] += tup.Item1[j];
}
if (!found)
{
break;
}
if (tup.Item2 <= 0.0)
{
if (res.initialUtil > 0.0)
{
res.initialUtil = tup.Item2;
}
else
{
res.initialUtil += tup.Item2;
}
}
}
//tup = term.Differentiate(res.initialValue);
} while(!found);
res.finalUtil = res.initialUtil;
Buffer.BlockCopy(res.initialValue, 0, res.finalValue, 0, sizeof(double) * dim);
return(gradient);
}