All Classes and Interfaces
Class
Description
An angle variable.
An assignment variable.
Provides methods for the Beta distribution, including CDF, PDF, PPF, and SF.
A random variable with a beta distribution.
A binary matrix variable: an
m by n matrix of binary variables.A binary N-dimensional variable: an array of binary variables with the shape
dims.The COptQuestBinaryVariable class defines a binary decision variable which is a
discrete variable that can have a value of 0 or 1.
A binary vector variable:
k binary variables.A B-spline correction matrix variable.
A B-spline correction vector variable.
A B-spline matrix variable.
A B-spline vector variable.
A budgeted selection variable.
A random variable with a Cauchy distribution.
Provides methods for the Chi-Square distribution: CDF, PDF, and PPF.
A random variable with a chi-squared distribution: the sum of the squares of
df independent standard normal values.A choice variable.
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.
A DAG variable.
Deprecated.
A discrete matrix variable: an
m by n matrix of discrete variables.A discrete N-dimensional variable: an array of discrete variables with the shape
dims.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
A discrete vector variable:
n discrete variables.The COptQuestDualRequirement defines a requirement that has both a lower bound
and an upper bound.
A decision variable that has an enumerated set of values such as 5,7 and
25.
The COptQuestEQConstraint class defines an equality linear constraint of the form
2*Var1 + 3*Var2 + 1.5*Var3 = 100
The COptQuestEquationSolver class provides methods to parse strings.
Exceptions thrown by the OptQuest Engine.
COptQuestExchangeableGroup is a set of identical items whose values you can exchange without a
change to the result.
Provides static methods for computing functions of the exponential distribution,
including the cumulative distribution function (CDF), probability density function (PDF),
percent point function (PPF), survival function (SF), hazard function (HAZ),
and cumulative hazard function (CHAZ).
A random variable with an exponential distribution: the time between
events that occur at random at a constant average rate.
COptQuestFixFloatGroup is a set of decision variables that the optimizer searches separately
from the other variables, near the best solution found so far.
A Fourier correction matrix variable.
A Fourier correction vector variable.
A Fourier matrix variable.
A Fourier vector variable.
With the COptQuestFrontierMultiObjective, the user can combine objectives and
treat them as a single objective for the optimization.
Provides static methods for gamma distribution functions:
CDF, PDF, PPF (inverse CDF), hazard, and cumulative hazard.
A random variable with a gamma distribution.
The COptQuestGEConstraint class defines a greater than or equal linear constraint
of the form 2*Var1 + 3*Var2 + 1.5*Var3 ≥ 100
A decision variable whose values are lists of latitude and longitude.
An incremental low-rank correction matrix variable.
An incremental time-series correction vector variable.
An integer matrix variable: an
m by n matrix of integer variables.An integer N-dimensional variable: an array of integer variables with the shape
dims.The COptQuestIntegerVariable class defines a decision variable whose values
begin at the lower bound and increment by a 1 to the upper bound.
An integer vector variable:
n integer variables.An item selection variable.
A generic structure to hold the candidate points for a max variance kriging
operation (See GeospataialSamplingGenerator)
An implementation of the most common use of the KrigEvaluator.
An implementation of KrigDistance that
returns the Euclidean distance between two vectors
A generic structure to hold the candidate points for a
max variance kriging operation (See GeospataialSamplingGenerator)
An implementation of KrigDistance that normalizes the variables to be on
[0,1] and computes the Euclidean distance after normalization.
A shared implementation of KrigDistance that handles different types of variables:
locations and "default", which is numeric.
An implementation of KrigDistance that normalizes the variables to be on
[0,1] and computes the Euclidean distance after normalization.
An implementation of KrigDistance that returns the "map distance" between two
vectors on the surface of a sphere.
A generic structure to hold the candidate points for a
max variance kriging operation (See GeospataialSamplingGenerator)
An implementation of a KrigTestPointSequence.
The COptQuestLEConstraint class defines a less than or equal linear constraint of
the form 2*Var1 + 3*Var2 + 1.5*Var3 ≤ 100
A random variable with a log-normal distribution: a value whose logarithm
has a normal distribution.
The COptQuestLowerRequirement defines a requirement that has a lower bound but
no upper bound.
A low-rank correction matrix variable.
A low-rank matrix variable.
Base class for the manifold variables.
A matrix variable: an
m by n matrix of continuous variables.Metalog (Meta-Logistic) distribution: a flexible quantile-parameterized distribution.
A mixture variable.
A multi-choice variable.
The COptQuestMultiObjective is an abstract class.
A multi-stage sequence variable.
An N-dimensional variable: an array of continuous variables with the shape
dims.A random variable with a normal distribution.
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.
You use the COptQuestOrConstraint class to define a logical "or" relationship
among COptQuestConstraint objects.
You use the COptQuestOrRequirement class to define a logical "or" relationship
among COptQuestRequirement objects.
An output N-dimensional variable: an array of output variables with the shape
dims.Provides methods for the Pareto distribution.
A random variable with a Pareto (Type I) distribution.
A partition variable.
A path variable.
Deprecated.
Use a sequence variable (
COptQuestSequenceVariable) instead.Deprecated.
Use a sequence variable (
COptQuestSequenceVariable) instead.A random variable with a Poisson distribution: the number of events in a
fixed interval, when the events occur at random at an average rate of
lambda for each
interval.A policy sequence variable.
A random variable whose value is from
rmin to rmax.A region variable.
The COptQuestRequirement class is a pure virtual class that you use to define
a non-linear constraint.
The COptQuestSearchParameters class contains values that control
the search algorithms.
Use COptQuestSelectionGroup to have a binary variable whose value indicates an on/off state,
where the off state indicates that other variables are not used in the evaluation.
A sequence variable.
A COptQuestSolution object contains the values for one solution and provides
methods to access information on the solution.
You use the COptQuestSolutionSet class to select a set of solutions
and perform statistical analysis or sensitivity analysis on the
set.
A spherical angle variable.
Probability distribution for the elevation angle when sampling points uniformly
on (a portion of) a sphere surface.
A random variable whose value is an elevation angle in degrees,
drawn uniformly by surface area from the band of the unit sphere between the elevations
min and max.A spherical region variable.
A spline correction matrix variable.
A spline correction vector variable.
A spline matrix variable.
A spline vector variable.
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.
Use COptQuestStringVariable to add a variable that is defined by an expression.
A random variable with a Student's t distribution.
A time-series correction vector variable.
A time-series vector variable.
A topological sequence variable.
A tree variable.
A decision variable whose values are lists of tuples.
A random variable with a uniform distribution on [
min, max].The COptQuestUpperRequirement defines a requirement that has an upper bound but
no lower bound.
An output matrix variable: an
m by n matrix of output variables.With the COptQuestUserControlledObjective, you compute a value for
the optimization objective.
The COptQuestUserControlledOptimization class searches for solutions to problems using a
'black box' approach.
With the COptQuestUserControlledVariable class, you define a variable and
set the value of the variable yourself.
An output vector variable:
n output variables.COptQuestVariable is a pure virtual class that defines a decision variable.
A vector variable:
n continuous variables.Provides static methods for computing various functions of the Weibull distribution.
A random variable with a Weibull distribution, in its minimum extreme value
form.
Deprecated.
A generic interface to return the generalized distance between two vectors.
A generic interface to return the generalized distance between two vectors.
ISolutionFilter is used to define a filter for a COptQuestSolutionSet object.
COptQuestChoiceVariable) instead.