public HyperParameterManagerTests()
{
hyperParams = new List <IVariable>();
values = new List <double>();
for (var i = 0; i < 3; i++)
{
hyperParams.Add(new VariableContinuous(name: Prefix + $"{i}"));
values.Add(i);
}
hyperParameters = new HyperParameterManager();
}
public EvolutionaryAlgorithmBuilderContinuousMO(
Population population,
DecisionSpace decisionSpace,
HyperParameterManager hyperParameters,
IParentSelectionOperator parentSelector,
IRecombinationOperator recombinationOperator,
IMutationOperator mutationOperator,
IReinsertionOperator reinsertionOperator)
{
this.decisionSpace = decisionSpace;
HyperParameters.AddFromExistingHyperParameterSet(hyperParameters);
this.population = population;
this.parentSelector = parentSelector;
this.recombinationOperator = recombinationOperator;
this.mutationOperator = mutationOperator;
this.reinsertionOperator = reinsertionOperator;
}
/// <summary>
/// Constructs a new Nelder-Mead Simplex local search optimiser.
/// </summary>
/// <param name="fitnessCalculator">A <see cref="FitnessCalculatorSingleObjective"/>. <see cref="Optimiser"/></param>
/// <param name="initialLocation">Starting location for the search.</param>
/// <param name="hyperParameters">
/// Instance of <see cref="HyperParameterManager"/> containing values for
/// all the coefficients required by <see cref="NelderMeadHyperParameters"/>.
/// </param>
public NelderMead(
IFitnessCalculator fitnessCalculator,
DecisionVector initialLocation,
HyperParameterManager hyperParameters) :
base(new Simplex(initialLocation.Count), fitnessCalculator)
{
// Set up simplex operations
OperationsManager = new NelderMeadSimplexOperationsManager(hyperParameters);
//Set up simplex
InitialVerticesStillUnevaluated = Simplex.CreateInitialVertices(
initialLocation,
hyperParameters.GetHyperParameterValue <double>(NelderMeadHyperParameters.Simplex_Creation_Step_Size));
//Initialise historian
tempProgress.Add(NelderMeadSimplexOperations.R);
}
public static HyperParameterManager GetDefaultHyperParameters()
{
var mgr = new HyperParameterManager();
mgr.AddOrReplaceHyperParameter(
new VariableDiscrete(5, 10000,
10, 1000,
Population_Size),
100);
mgr.AddOrReplaceHyperParameter(
new VariableDiscrete(2, 1000,
2, 200,
Number_Of_Parents),
40);
return(mgr);
}
/// <summary>
/// Creates an Evolutionary Algorithm.
/// </summary>
/// <param name="initialPopulation">The initial population (can be empty).</param>
/// <param name="fitnessCalculator">A <see cref="FitnessCalculatorSingleObjective"/>. <see cref="Optimiser"/></param>
/// <param name="initialIndividualGenerator">Creates new decision vectors to build the first population. <seealso cref="Base.Conversion.IModel"/></param>
/// <param name="parentSelector">The <see cref="IParentSelectionOperator"/> to use.</param>
/// <param name="recombinationOperator">The <see cref="IRecombinationOperator"/> to use.</param>
/// <param name="mutationOperator">The <see cref="IMutationOperator"/> to use.</param>
/// <param name="reinsertionOperator">The <see cref="IReinsertionOperator"/> to use.</param>
/// <param name="hyperParameters">The <see cref="HyperParameterManager"/> object with relevant settings.</param>
public EvolutionaryAlgorithm(
Population initialPopulation,
IFitnessCalculator fitnessCalculator,
Func <DecisionVector> initialIndividualGenerator,
IParentSelectionOperator parentSelector,
IRecombinationOperator recombinationOperator,
IMutationOperator mutationOperator,
IReinsertionOperator reinsertionOperator,
HyperParameterManager hyperParameters)
: base(initialPopulation, fitnessCalculator)
{
this.initialIndividualGenerator = initialIndividualGenerator;
this.parentSelector = parentSelector;
numberOfParents = hyperParameters.GetHyperParameterValue <int>(EvolutionaryAlgorithmHyperParameters.Number_Of_Parents);
this.recombinationOperator = recombinationOperator;
this.mutationOperator = mutationOperator;
this.reinsertionOperator = reinsertionOperator;
}
public static HyperParameterManager GetDefaultHyperParameters()
{
var mgr = new HyperParameterManager();
mgr.AddOrReplaceHyperParameter(
new VariableContinuous(0.001, 100,
0.001, 100,
Simplex_Creation_Step_Size),
0.5);
mgr.AddOrReplaceHyperParameter(
new VariableContinuous(0.001, double.MaxValue,
0.5, 2,
Reflection_Coefficient),
1.0);
mgr.AddOrReplaceHyperParameter(
new VariableContinuous(1.001, double.MaxValue,
1.1, 5,
Expansion_Coefficient),
2.0);
mgr.AddOrReplaceHyperParameter(
new VariableContinuous(0.001, 1.0,
0.01, 0.9,
Contraction_Coefficient),
0.5);
mgr.AddOrReplaceHyperParameter(
new VariableContinuous(0.001, 1.0,
0.01, 0.9,
Shrinkage_Coefficient),
0.5);
return(mgr);
}
public NelderMeadBuilder(DecisionSpace decisionSpace, HyperParameterManager hyperParameters)
{
this.decisionSpace = decisionSpace;
HyperParameters.AddFromExistingHyperParameterSet(hyperParameters);
}
