fr.cnes.sirius.patrius.math.optim.joptimizer.optimizers

Class OptimizationRequest

java.lang.Object

fr.cnes.sirius.patrius.math.optim.joptimizer.optimizers.OptimizationRequest

Direct Known Subclasses:

LPOptimizationRequest

public class OptimizationRequest
extends Object

Optimization problem. Setting the field's values you define an optimization problem.

Since:

4.6

Author:

alberto trivellato (alberto.trivellato@gmail.com) HISTORY VERSION:4.6:DM:DM-2591:27/01/2021:[PATRIUS] Intigration et validation JOptimizer END-HISTORY

See Also:

"S.Boyd and L.Vandenberghe, Convex Optimization"

Constructor Summary

Constructors

Constructor and Description
OptimizationRequest()

Method Summary

Modifier and Type	Method and Description
RealMatrix	getA() Get the equalities constraints matrix
double	getAlpha() Get the calibration parameter for line search
RealVector	getB() Get the equalities constraints vector
double	getBeta() Get the calibration parameter for line search
ConvexMultivariateRealFunction	getF0() Get the objective function to minimize
ConvexMultivariateRealFunction[]	getFi() Get the inequalities constraints array
RealVector	getInitialLagrangian() Get a starting point for the Lagrangian multipliers
RealVector	getInitialPoint() Get the feasible starting point for the minimum search
String	getInteriorPointMethod() Get the chosen interior-point method
int	getMaxIteration() Get the maximum number of iteration in the search algorithm.
double	getMu() Get the calibration parameter for line search
RealVector	getNotFeasibleInitialPoint() Get a not-feasible starting point for the minimum search
double	getTolerance() Get the tolerance for the minimum value.
double	getToleranceFeas() Get the tolerance for the constraints satisfaction.
double	getToleranceInnerStep() Get the tolerance for inner iterations in the barrier-method.
double	getToleranceKKT() Get the acceptable tolerance for KKT system resolution
boolean	isCheckKKTSolutionAccuracy() Check the accuracy of the solution of KKT system during iterations.
boolean	isCheckProgressConditions() If true, a progress in the relevant algorithm norms is required during iterations, otherwise the iteration will be exited with a warning
boolean	isRescalingDisabled() Is the matrix rescaling disabled?
void	setA(double[][] a) Set the equalities constraints matrix
void	setA(RealMatrix a) Set the equalities constraints matrix
void	setAlpha(double a) Set the calibration parameter for line search
void	setB(double[] vecB) Set the equalities constraints vector
void	setB(RealVector vecB) Set the equalities constraints vector
void	setBeta(double be) Set the calibration parameter for line search
void	setCheckKKTSolutionAccuracy(boolean checkKKTSolutionAcc) Set true if every inversion of the system must have an accuracy that satisfy the given toleranceKKT, false otherwise.
void	setCheckProgressConditions(boolean checkProgressCondition) Set true if a progress in the relevant algorithm norms is required during iterations, or false if the iteration will be exited with a warning
void	setF0(ConvexMultivariateRealFunction f) Set the objective function to minimize
void	setFi(ConvexMultivariateRealFunction[] f) Set the inequalities constraints array
void	setInitialLagrangian(double[] initialL) Set a starting point for the Lagrangian multipliers
void	setInitialPoint(double[] initialP) Set the feasible starting point for the minimum search
void	setInteriorPointMethod(String interiorPM) Set the chosen interior-point method
void	setMaxIteration(int maxIterations) Set the maximum number of iteration in the search algorithm.
void	setMu(double m) Set the calibration parameter for line search
void	setNotFeasibleInitialPoint(double[] notFeasibleInitialP) Set a not-feasible starting point for the minimum search
void	setRescalingDisabled(boolean rescalingDis) Set if the matrix rescaling should be disabled (true) or not (false) Rescaling is involved in LP presolving and in the solution of the KKT systems associated with the problem.
void	setTolerance(double toleranceMV) Set the tolerance for the minimum value.
void	setToleranceFeas(double toleranceF) Set the tolerance for the constraints satisfaction.
void	setToleranceInnerStep(double toleranceIS) Set the tolerance for inner iterations in the barrier-method.
void	setToleranceKKT(double toleranceK) Set the acceptable tolerance for KKT system resolution

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

OptimizationRequest

public OptimizationRequest()

Method Detail

getMaxIteration

public int getMaxIteration()

Get the maximum number of iteration in the search algorithm.

Returns:

maximum number of iteration

setMaxIteration

public void setMaxIteration(int maxIterations)

Set the maximum number of iteration in the search algorithm.

Parameters:

maxIterations - maximum number of iteration

getTolerance

public double getTolerance()

Get the tolerance for the minimum value.

Returns:

tolerance

setTolerance

public void setTolerance(double toleranceMV)

Set the tolerance for the minimum value.

Parameters:

toleranceMV - tolerance

getToleranceFeas

public double getToleranceFeas()

Get the tolerance for the constraints satisfaction.

Returns:

tolerance

setToleranceFeas

public void setToleranceFeas(double toleranceF)

Set the tolerance for the constraints satisfaction.

Parameters:

toleranceF - tolerance

getToleranceInnerStep

public double getToleranceInnerStep()

Get the tolerance for inner iterations in the barrier-method.

Returns:

tolerance

setToleranceInnerStep

public void setToleranceInnerStep(double toleranceIS)

Set the tolerance for inner iterations in the barrier-method.

Parameters:

toleranceIS - tolerance

getAlpha

public double getAlpha()

Get the calibration parameter for line search

Returns:

alpha

setAlpha

public void setAlpha(double a)

Set the calibration parameter for line search

Parameters:

a - calibration parameter

getBeta

public double getBeta()

Get the calibration parameter for line search

Returns:

beta

setBeta

public void setBeta(double be)

Set the calibration parameter for line search

Parameters:

be - calibration parameter

getMu

public double getMu()

Get the calibration parameter for line search

Returns:

mu

setMu

public void setMu(double m)

Set the calibration parameter for line search

Parameters:

m - calibration parameter

isCheckProgressConditions

public boolean isCheckProgressConditions()

If true, a progress in the relevant algorithm norms is required during iterations, otherwise the iteration will be exited with a warning

Returns:

true/false

setCheckProgressConditions

public void setCheckProgressConditions(boolean checkProgressCondition)

Set true if a progress in the relevant algorithm norms is required during iterations, or false if the iteration will be exited with a warning

Parameters:

checkProgressCondition - true/false

isCheckKKTSolutionAccuracy

public boolean isCheckKKTSolutionAccuracy()

Check the accuracy of the solution of KKT system during iterations. If true, every inversion of the system must have an accuracy that satisfy the given toleranceKKT

Returns:

true/false

setCheckKKTSolutionAccuracy

public void setCheckKKTSolutionAccuracy(boolean checkKKTSolutionAcc)

Set true if every inversion of the system must have an accuracy that satisfy the given toleranceKKT, false otherwise.

Parameters:

checkKKTSolutionAcc - true/false

getToleranceKKT

public double getToleranceKKT()

Get the acceptable tolerance for KKT system resolution

Returns:

tolerance

setToleranceKKT

public void setToleranceKKT(double toleranceK)

Set the acceptable tolerance for KKT system resolution

Parameters:

toleranceK - tolerance

getF0

public ConvexMultivariateRealFunction getF0()

Get the objective function to minimize

Returns:

objective function

setF0

public void setF0(ConvexMultivariateRealFunction f)

Set the objective function to minimize

Parameters:

f - objective function

getInitialPoint

public RealVector getInitialPoint()

Get the feasible starting point for the minimum search

Returns:

initial point

setInitialPoint

public void setInitialPoint(double[] initialP)

Set the feasible starting point for the minimum search

Parameters:

initialP - feasible starting point

getNotFeasibleInitialPoint

public RealVector getNotFeasibleInitialPoint()

Get a not-feasible starting point for the minimum search

Returns:

not-feasible initial point

setNotFeasibleInitialPoint

public void setNotFeasibleInitialPoint(double[] notFeasibleInitialP)

Set a not-feasible starting point for the minimum search

Parameters:

notFeasibleInitialP - not-feasible initial point

getInitialLagrangian

public RealVector getInitialLagrangian()

Get a starting point for the Lagrangian multipliers

Returns:

initial point

setInitialLagrangian

public void setInitialLagrangian(double[] initialL)

Set a starting point for the Lagrangian multipliers

Parameters:

initialL - initial point

getA

public RealMatrix getA()

Get the equalities constraints matrix

Returns:

equalities constraints matrix

setA

public void setA(double[][] a)

Set the equalities constraints matrix

Parameters:

a - equalities constraints double[][]

setA

public void setA(RealMatrix a)

Set the equalities constraints matrix

Parameters:

a - equalities constraints matrix

getB

public RealVector getB()

Get the equalities constraints vector

Returns:

equalities constraints vector

setB

public void setB(double[] vecB)

Set the equalities constraints vector

Parameters:

vecB - equalities constraints double[]

setB

public void setB(RealVector vecB)

Set the equalities constraints vector

Parameters:

vecB - equalities constraints vector

getFi

public ConvexMultivariateRealFunction[] getFi()

Get the inequalities constraints array

Returns:

inequalities constraints array

setFi

public void setFi(ConvexMultivariateRealFunction[] f)

Set the inequalities constraints array

Parameters:

f - inequalities constraints array

getInteriorPointMethod

public String getInteriorPointMethod()

Get the chosen interior-point method

Returns:

chosen interior-point method

setInteriorPointMethod

public void setInteriorPointMethod(String interiorPM)

Set the chosen interior-point method

Parameters:

interiorPM - chosen interior-point method (string)

setRescalingDisabled

public void setRescalingDisabled(boolean rescalingDis)

Set if the matrix rescaling should be disabled (true) or not (false) Rescaling is involved in LP presolving and in the solution of the KKT systems associated with the problem.

Parameters:

rescalingDis - true/false

isRescalingDisabled

public boolean isRescalingDisabled()

Is the matrix rescaling disabled?

Returns:

true/false