protected override Chromosome GetBestFromPopulation(Population <Chromosome, BinaryRepresentation> population)
{
var populationMinimum = population.Chromosomes.Min(c =>
optimizingFunction.GetValue(c, new ChromosomeToDoubleSetConverter()));
return(population.Chromosomes.First(
c => optimizingFunction.GetValue(c, new ChromosomeToDoubleSetConverter()) == populationMinimum));
}
public double Build()
{
function.Precision = precision;
var minimum = double.MaxValue;
for (var currentIteration = 1; currentIteration <= iterations; currentIteration++)
{
var randomState =
DomainHelper.RandomDimensionalBinaryValueInDomainRange(
function.GetDomain(),
function.GetDimensionDefinition(),
precision);
var neighboursExhausted = false;
while (!neighboursExhausted)
{
var neighbourhood = GetNeighbourhood(randomState);
var improvement = strategy.PickImprovement(neighbourhood, function, minimum);
if (improvement == null)
{
neighboursExhausted = true;
}
else
{
minimum = function.GetValue(improvement, new BinarySetToDoubleSetConverter());
}
}
}
return(minimum);
}
public override DimensionSet <BinaryRepresentation> PickImprovement(
IEnumerable <DimensionSet <BinaryRepresentation> > neighbourhood,
DimensionalFunction function,
double currentMinimum)
{
return(neighbourhood.FirstOrDefault(n => function.GetValue(n, new BinarySetToDoubleSetConverter()) < currentMinimum));
}
public override DimensionSet <double> PickImprovement(
IEnumerable <DimensionSet <double> > neighbourhood,
DimensionalFunction function,
double currentMinimum)
{
return(neighbourhood.FirstOrDefault(n => function.GetValue(n) < currentMinimum));
}
public double Build()
{
var temperature = startingTemperature;
function.Precision = precision;
var minimum = double.MaxValue;
var currentState =
DomainHelper.RandomDimensionalBinaryValueInDomainRange(function.GetDomain(), function.GetDimensionDefinition(), precision);
while (temperature > minimumTemperature)
{
var neighbour = GetNeighbour(currentState);
var neighbourValue = function.GetValue(neighbour, new BinarySetToDoubleSetConverter());
var randomNumber = new Random().NextDouble();
if (minimum > neighbourValue || randomNumber < Math.Exp((neighbourValue - minimum) / temperature))
{
minimum = neighbourValue;
currentState = neighbour;
}
temperature *= alpha;
}
return(minimum);
}
public double Build()
{
var currentMinimum = double.MaxValue;
for (var currentTry = 1.0; currentTry <= randomTriesCount; currentTry += step)
{
var functionParameters =
DomainHelper.RandomDimensionalValueInDomainRange(function.GetDomain(), function.GetDimensionDefinition());
var functionValue = function.GetValue(functionParameters);
currentMinimum = TestMinimum(currentMinimum, functionValue);
}
return(currentMinimum);
}
public override DimensionSet <BinaryRepresentation> PickImprovement(
IEnumerable <DimensionSet <BinaryRepresentation> > neighbourhood,
DimensionalFunction function,
double currentMinimum)
{
DimensionSet <BinaryRepresentation> bestImprovement = null;
foreach (var neighbour in neighbourhood)
{
var value = function.GetValue(neighbour, new BinarySetToDoubleSetConverter());
if (currentMinimum <= value)
{
continue;
}
currentMinimum = value;
bestImprovement = neighbour;
}
return(bestImprovement);
}
public override DimensionSet <double> PickImprovement(
IEnumerable <DimensionSet <double> > neighbourhood,
DimensionalFunction function,
double currentMinimum)
{
DimensionSet <double> bestImprovement = null;
foreach (var neighbour in neighbourhood)
{
var value = function.GetValue(neighbour);
if (currentMinimum <= value)
{
continue;
}
currentMinimum = value;
bestImprovement = neighbour;
}
return(bestImprovement);
}