The COptQuestCompoundConstraint is a pure virtual class.
COptQuestConstraint is a pure virtual class that defines a linear constraint.
The COptQuestContinuousVariable class defines a decision variable that can have
any value between the lower bound and upper bound.
The CoptQuestDiscreteVariable class defines a decision variable whose values
begin at the lower bound and increment by a step size up to the upper bound
Exceptions thrown by the OptQuest Engine.
COptQuestExchangeableGroup allows the user to create groups of variables that are identical under exchange.
A generic structure to hold the candidate points for a max variance kriging
operation (See GeospataialSamplingGenerator)
A generic structure to hold the candidate points for a
max variance kriging operation (See GeospataialSamplingGenerator)
An shared implementation of KrigDistance that handles different types of variables:
right now we handle locations and "default" which is just numeric.
A generic structure to hold the candidate points for a
max variance kriging operation (See GeospataialSamplingGenerator)
The COptQuestMultiObjective is an abstract class.
The COptQuestObjective class is a pure virtual class that defines the objective
of the optimization.
The COptQuestObjectiveFunction class is used to define a linear objective.
The COptQuestOptimization class searches for solutions to problems using a
'black box' approach.
The COptQuestOrRequirement class allows you to define a logical "or" relationship
among COptQuestRequirement objects.
This class allows users to add groups of permutation variables to an
optimization problem.
Permutation variables are used to solve sequencing problems.
The COptQuestRequirement class is a pure virtual class that allows you to define
a non-linear constraint.
The COptQuestSearchParameters class contains values that control
the search algorithms.
COptQuestSelectionGroup allows the user to have a binary variable who value indicates an on/off state,
where the off state indicates that other variables are not used in the evaluation.
A COptQuestSolution object contains the values for one solution and provides
methods to access information on the solution.
The COptQuestSolutionSet class allows you to select a set of solutions
and perform statistical analysis or sensitivity analysis on the
set.
The COptQuestStringConstraint class is used to define linear and non-linear
constraints using a mathematical expression.
The COptQuestStringObjective class is used to define an objective function
using a mathematical expression.
The COptQuestTupleVariable class defines a decision variable whose values
are lists of tuples.
The COptQuestUserControlledObjective allows you to compute a value for
the optimization objective.
The COptQuestUserControlledVariable class allows you to define a variable where
you set the value of the variable.
COptQuestVariable is a pure virtual class that defines a decision variable.
A generic interface to return the generalized distance between two vectors
For Kriging, we need to know the distance between two vectors.
ISolutionFilter is used to define a filter for a COptQuestSolutionSet object.
Inspired from: Numerical Recipes in C++ The Art of Scientific Computing Third
Edition 2007
This is the main implementation of the Kriging algorithm.
OptQuestDefinition holds the data members that define an optimization
problem.