public ElitismOpr(OptimisationTemplate Template, GAParameters gaParameters, Population.Population parentPopulation, Population.Population childPopulation)
{
this.Template = Template;
this.gaParameters = gaParameters;
this.parentPopulation = parentPopulation;
this.childPopulation = childPopulation;
}
public SingleObjectivePopulation(OptimisationTemplate Template, GAParameters gaParameters, int populationSize, bool empty)
: base(Template, gaParameters, populationSize)
{
//initialising population chromosomes
chromosomes = new SingleObjectiveChromosome[populationSize];
for (int i = 0; i < Size; i++)
{
chromosomes[i] = new SingleObjectiveChromosome(Template, gaParameters, empty);
}
//initialising best chromosome
bestChromosome = new SingleObjectiveChromosome(Template, gaParameters, true);
}
public MultiObjectivePopulation(OptimisationTemplate Template, GAParameters gaParameters, int populationSize, bool empty)
: base(Template, gaParameters, populationSize)
{
//initialising population chromosomes
chromosomes = new MultiObjectiveChromosome[size];
for (int i = 0; i < size; i++)
{
chromosomes[i] = new MultiObjectiveChromosome(Template, gaParameters, empty);
}
//initialising the seven statistics variables
int noOfObjectives = Template.Objectives.Count;
bestObjectives = new double[noOfObjectives];
worstObjectives = new double[noOfObjectives];
averageObjectives = new double[noOfObjectives];
maximumFitnesses = new double[noOfObjectives];
minimumFitnesses = new double[noOfObjectives];
averageFitnesses = new double[noOfObjectives];
fitnessVariances = new double[noOfObjectives];
}
public Chromosome(OptimisationTemplate Template, GAParameters gaParameters, bool empty)
{
this.Template = Template;
this.gaParameters = gaParameters;
int noOfDesignVariables = Template.DesignVariables.Count;
genes = new double[noOfDesignVariables];
for (int i = 0; i < noOfDesignVariables; i++)
{
if (Template.DesignVariables[i].Type == DesignVariableType.Integer)
{
if (!empty)
{
genes[i] = GARandom.BoundedRandomInteger((int)Template.DesignVariables[i].LowerBound, (int)Template.DesignVariables[i].UpperBound);
}
else
{
genes[i] = 0.0;
}
}
if (Template.DesignVariables[i].Type == DesignVariableType.Double)
{
if (!empty)
{
genes[i] = GARandom.BoundedRandomDouble(Template.DesignVariables[i].LowerBound, Template.DesignVariables[i].UpperBound);
}
else
{
genes[i] = 0.0;
}
}
}
constraintValues = new double[Template.Constraints.Count];
constraintViolationValues = new double[Template.Constraints.Count];
}
public RobustOptimisationStudy(string name, Treatment treatment, ExecutableComponent ec, OptimisationTemplate template, string parentName = "")
: base(name, null, null, name, parentName)
{
Treatment = treatment;
StudiedComponent = ec;
var DesignVariables = template.DesignVariables.Select(v => new RobOptDesignVariable {
Name = v.Name
}).ToList();
var Objectives = template.Objectives.Select(o => new RobOptObjective {
Name = o.Name, Type = o.Type
}).ToList();
var Constraints = template.Constraints.Select(c => new RobOptConstraint {
Name = c.Name, Type = c.Type, Value = c.Value
}).ToList();
robOptTemplate = new RobOptTemplate()
{
DesignVariables = DesignVariables, Objectives = Objectives, Constraints = Constraints
};
ColumnNames.Add("ID");
ColumnTypes.Add(DataTypes.INTEGER);
ColumnFormats.Add(0);
ColumnUnits.Add("");
for (int i = 0; i < robOptTemplate.DesignVariables.Count(); i++)
{
string columnHeader = robOptTemplate.DesignVariables[i].Name;
ColumnNames.Add(columnHeader);
ColumnTypes.Add(DataTypes.DOUBLE);
ColumnFormats.Add(4);
ColumnUnits.Add("");
}
for (int i = 0; i < robOptTemplate.Objectives.Count(); i++)
{
string columnHeader = robOptTemplate.Objectives[i].Name;
// Loss Function
ColumnNames.Add(columnHeader + "LF");
ColumnTypes.Add(DataTypes.DOUBLE);
ColumnFormats.Add(4);
ColumnUnits.Add("");
// Mean
ColumnNames.Add(columnHeader + "mean");
ColumnTypes.Add(DataTypes.DOUBLE);
ColumnFormats.Add(4);
ColumnUnits.Add("");
// Variance
ColumnNames.Add(columnHeader + "var");
ColumnTypes.Add(DataTypes.DOUBLE);
ColumnFormats.Add(4);
ColumnUnits.Add("");
}
for (int i = 0; i < robOptTemplate.Constraints.Count(); i++)
{
string columnHeader = robOptTemplate.Constraints[i].Name;
// Loss Function
ColumnNames.Add(columnHeader + "LF");
ColumnTypes.Add(DataTypes.DOUBLE);
ColumnFormats.Add(4);
ColumnUnits.Add("");
// Mean
ColumnNames.Add(columnHeader + "mean");
ColumnTypes.Add(DataTypes.DOUBLE);
ColumnFormats.Add(4);
ColumnUnits.Add("");
// Variance
ColumnNames.Add(columnHeader + "var");
ColumnTypes.Add(DataTypes.DOUBLE);
ColumnFormats.Add(4);
ColumnUnits.Add("");
}
TableNames.Add("RobOptimAllResults");
TableNames.Add("RobOptimGenResults");
Template = template;
}
public Population(OptimisationTemplate Template, GAParameters gaParameters)
: this(Template, gaParameters, gaParameters.PopulationSize)
{
}
public MultiObjectivePopulation(OptimisationTemplate Template, GAParameters gaParameters, bool empty)
: this(Template, gaParameters, gaParameters.PopulationSize, empty)
{
}
public MutationOpr(OptimisationTemplate Template, GAParameters gaParameters)
{
this.Template = Template;
this.gaParameters = gaParameters;
}
public DetOptStudy(string name, string description, ExecutableComponent studiedComponent, OptimisationTemplate optimisationTemplate, Treatment treatment, string parentName = "")
: base(name, null, null, description, parentName)
{
OptimisationTemplate = optimisationTemplate;
base.Treatment = treatment;
StudiedComponent = studiedComponent;
// Create SQL statements to create tables, sqlStatement1 for OptimAllResults and sqlStatement2 for OptimGenResults
sqlStatement1 = "create table OptimAllResults (";
sqlStatement2 = "create table OptimGenResults (";
sqlStatement1 += "ID int, ";
sqlStatement2 += "ID int, Category int, ";
#region Atif
// Prepare results database
foreach (BoundedDesignVariableNoInital designVariable in this.OptimisationTemplate.DesignVariables)
{
string columnHeader = designVariable.Name;
ColumnNames.Add(columnHeader);
sqlStatement1 += columnHeader + " ";
sqlStatement2 += columnHeader + " ";
if (designVariable.Data is IntegerData)
{
ColumnTypes.Add(DataTypes.INTEGER);
ColumnFormats.Add(0);
sqlStatement1 += "int, ";
sqlStatement2 += "int, ";
}
else if (designVariable.Data is DoubleData)
{
ColumnTypes.Add(DataTypes.DOUBLE);
ColumnFormats.Add(((DoubleData)(designVariable.Data)).DecimalPlaces);
sqlStatement1 += "float, ";
sqlStatement2 += "float, ";
}
ColumnUnits.Add(designVariable.Data.Unit);
MinValues.Add(designVariable.LowerBound);
MaxValues.Add(designVariable.UpperBound);
}
foreach (Objective objective in this.OptimisationTemplate.Objectives)
{
string columnHeader = objective.Name;
ColumnNames.Add(columnHeader);
sqlStatement1 += columnHeader + " ";
sqlStatement2 += columnHeader + " ";
if (objective.Data is IntegerData)
{
ColumnTypes.Add(DataTypes.INTEGER);
ColumnFormats.Add(0);
sqlStatement1 += "int, ";
sqlStatement2 += "int, ";
}
else if (objective.Data is DoubleData)
{
ColumnTypes.Add(DataTypes.DOUBLE);
ColumnFormats.Add(((DoubleData)(objective.Data)).DecimalPlaces);
sqlStatement1 += "float, ";
sqlStatement2 += "float, ";
}
ColumnUnits.Add(objective.Data.Unit);
MinValues.Add(Double.NaN);
MaxValues.Add(Double.NaN);
}
foreach (Aircadia.ObjectModel.Treatments.Optimisers.Formulation.Constraint constraint in this.OptimisationTemplate.Constraints)
{
string columnHeader = constraint.Name;
ColumnNames.Add(columnHeader);
sqlStatement1 += columnHeader + " ";
sqlStatement2 += columnHeader + " ";
if (constraint.Data is IntegerData)
{
ColumnTypes.Add(DataTypes.INTEGER);
ColumnFormats.Add(0);
sqlStatement1 += "int, ";
sqlStatement2 += "int, ";
}
else if (constraint.Data is DoubleData)
{
ColumnTypes.Add(DataTypes.DOUBLE);
ColumnFormats.Add(((DoubleData)(constraint.Data)).DecimalPlaces);
sqlStatement1 += "float, ";
sqlStatement2 += "float, ";
}
ColumnUnits.Add(constraint.Data.Unit);
MinValues.Add(Double.NaN);
MaxValues.Add(Double.NaN);
}
TableNames.Add("OptimAllResults");
TableNames.Add("OptimGenResults");
if (this.OptimisationTemplate.DesignVariables.Count() + this.OptimisationTemplate.Objectives.Count() + this.OptimisationTemplate.Constraints.Count() > 0)
{
sqlStatement1 = sqlStatement1.Remove(sqlStatement1.Length - 2);
sqlStatement2 = sqlStatement2.Remove(sqlStatement2.Length - 2);
}
sqlStatement1 += ")";
sqlStatement2 += ")";
#endregion Atif
Treatment.CreateFolder();
}
public TournamentSelectionOpr(OptimisationTemplate Template, GAParameters gaParameters, int tournamentSize)
: base(Template, gaParameters)
{
this.tournamentSize = tournamentSize;
}
public TournamentSelectionOprWithoutReplacement(OptimisationTemplate Template, GAParameters gaParameters, int tournamentSize)
: base(Template, gaParameters, tournamentSize)
{
}
public SimulatedBinaryCrossoverOpr(OptimisationTemplate Template, GAParameters gaParameters)
: this(Template, gaParameters, 0.5, 10)
{
}
public Population(OptimisationTemplate Template, GAParameters gaParameters, int size)
{
this.Template = Template;
this.gaParameters = gaParameters;
this.size = size;
}
public SelectiveMutationOpr(OptimisationTemplate Template, GAParameters gaParameters)
: base(Template, gaParameters)
{
}
protected SelectionOpr(OptimisationTemplate Template, GAParameters gaParameters)
{
this.Template = Template;
this.gaParameters = gaParameters;
}
public OnePointCrossoverOpr(OptimisationTemplate Template, GAParameters gaParameters)
: base(Template, gaParameters)
{
}
public CrossoverOpr(OptimisationTemplate Template, GAParameters gaParameters)
{
this.Template = Template;
this.gaParameters = gaParameters;
}
public ProportionalElitismOpr(OptimisationTemplate Template, GAParameters gaParameters, Population.Population parentPopulation, Population.Population childPopulation)
: base(Template, gaParameters, parentPopulation, childPopulation)
{
}
protected double crowdingDistance; //will be initialised to 0.0 upon object creation
public MultiObjectiveChromosome(OptimisationTemplate Template, GAParameters gaParameters, bool empty)
: base(Template, gaParameters, empty)
{
objectiveValues = new double[Template.Objectives.Count];
fitnessValues = new double[Template.Objectives.Count];
}
public TournamentSelectionOprWithoutReplacement(OptimisationTemplate Template, GAParameters gaParameters)
: this(Template, gaParameters, 2)
{
}
public GAParameters(OptimisationTemplate template) : this(template.Constraints.Count)
{
}
public SimulatedBinaryCrossoverOpr(OptimisationTemplate Template, GAParameters gaParameters, double genewiseSwapProb, int polynomialOrder)
: base(Template, gaParameters)
{
this.genewiseSwapProb = genewiseSwapProb;
this.polynomialOrder = polynomialOrder;
}
public PolynomialMutationOpr(OptimisationTemplate Template, GAParameters gaParameters)
: base(Template, gaParameters)
{
}
public SingleObjectiveChromosome(OptimisationTemplate Template, GAParameters gaParameters, bool empty)
: base(Template, gaParameters, empty)
{
}
public GASetup(OptimisationTemplate template)
{
InitializeComponent();
gaParameters = new GAParameters(template);
}
