Package org.hipparchus.optim.nonlinear.vector.constrained

Class ADMMQPOption

java.lang.Object
org.hipparchus.optim.nonlinear.vector.constrained.ADMMQPOption
All Implemented Interfaces:
OptimizationData
public class ADMMQPOption extends Object implements OptimizationData
Container for ADMMQPOptimizer settings.
Since:
3.1

  • Field Summary

    Fields
    Modifier and Type
    Field
    Description
    static final double
    DEFAULT_ALPHA
    Default Value of Alpha filter for ADMM iteration.
    static final double
    DEFAULT_EPS
    Default Absolute and Relative Tolerance for convergence.
    static final double
    DEFAULT_EPS_INFEASIBLE
    Default Absolute and Relative Tolerance for Infeasible Criteria.
    static final int
    DEFAULT_MAX_RHO_ITERATION
    Default Max number of weight changes.
    static final boolean
    DEFAULT_POLISHING
    Default Value for enabling polishing the solution.
    static final int
    DEFAULT_POLISHING_ITERATION
    Default Value for Iteration of polishing Algorithm.
    static final double
    DEFAULT_RHO_MAX
    Default Max Value for the Weight for ADMM iteration.
    static final double
    DEFAULT_RHO_MIN
    Default Min Value for the Weight for ADMM iteration.
    static final boolean
    DEFAULT_RHO_UPDATE
    Default Value for adapting the weight during iterations.
    static final boolean
    DEFAULT_SCALING
    Default Value for Enabling Problem Scaling.
    static final int
    DEFAULT_SCALING_MAX_ITERATION
    Default Value for the Max Iteration for the scaling.
    static final double
    DEFAULT_SIGMA
    Default Value of regularization term sigma for Karush–Kuhn–Tucker solver.

  • Constructor Summary

    Constructors
    Constructor
    Description
    ADMMQPOption()
    Simple constructor.

  • Method Summary

    Modifier and Type
    Method
    Description
    double
    getAlpha()
    Get value of alpha filter for ADMM iteration.
    double
    getEps()
    Get absolute and Relative Tolerance for convergence.
    double
    getEpsInfeasible()
    Get absolute and Relative Tolerance for infeasible criteria.
    int
    getMaxRhoIteration()
    Get max number of weight changes.
    int
    getPolishIteration()
    Get number of iterations of polishing algorithm.
    double
    getRhoMax()
    Get max Value for the Weight for ADMM iteration.
    double
    getRhoMin()
    Get min Value for the Weight for ADMM iteration.
    int
    getScaleMaxIteration()
    Get max iteration for the scaling.
    double
    getSigma()
    Get value of regularization term sigma for Karush–Kuhn–Tucker solver.
    boolean
    isPolishing()
    Check if polishing is enabled.
    boolean
    isScaling()
    Check if scaling is enabled.
    void
    setAlpha(double alpha)
    Set value of alpha filter for ADMM iteration.
    void
    setEps(double eps)
    Set absolute and Relative Tolerance for convergence.
    void
    setEpsInfeasible(double epsInfeasible)
    Set absolute and Relative Tolerance for infeasible criteria.
    void
    setMaxRhoIteration(int maxRhoIteration)
    Set max number of weight changes.
    void
    setPolishing(boolean polishing)
    Set polishing enabling flag.
    void
    setPolishingIteration(int polishingIteration)
    Set number of iterations of polishing algorithm.
    void
    setRhoMax(double rhoMax)
    Set max Value for the Weight for ADMM iteration.
    void
    setRhoMin(double rhoMin)
    Set min Value for the Weight for ADMM iteration.
    void
    setScaleMaxIteration(int scaleMaxIteration)
    Set max iteration for the scaling.
    void
    setScaling(boolean scaling)
    Set scaling enabling flag.
    void
    setSigma(double sigma)
    Set value of regularization term sigma for Karush–Kuhn–Tucker solver.
    void
    setUpdateRho(boolean updateRho)
    Set weight updating flag.
    boolean
    updateRho()
    Check if weight updating is enabled.

    Methods inherited from class java.lang.Object

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

  • Field Details

    • DEFAULT_EPS

      public static final double DEFAULT_EPS
      Default Absolute and Relative Tolerance for convergence.
      See Also:

    • DEFAULT_EPS_INFEASIBLE

      public static final double DEFAULT_EPS_INFEASIBLE
      Default Absolute and Relative Tolerance for Infeasible Criteria.
      See Also:

    • DEFAULT_SIGMA

      public static final double DEFAULT_SIGMA
      Default Value of regularization term sigma for Karush–Kuhn–Tucker solver.
      See Also:

    • DEFAULT_ALPHA

      public static final double DEFAULT_ALPHA
      Default Value of Alpha filter for ADMM iteration.
      See Also:

    • DEFAULT_SCALING

      public static final boolean DEFAULT_SCALING
      Default Value for Enabling Problem Scaling.
      See Also:

    • DEFAULT_SCALING_MAX_ITERATION

      public static final int DEFAULT_SCALING_MAX_ITERATION
      Default Value for the Max Iteration for the scaling.
      See Also:

    • DEFAULT_RHO_UPDATE

      public static final boolean DEFAULT_RHO_UPDATE
      Default Value for adapting the weight during iterations.
      See Also:

    • DEFAULT_RHO_MAX

      public static final double DEFAULT_RHO_MAX
      Default Max Value for the Weight for ADMM iteration.
      See Also:

    • DEFAULT_RHO_MIN

      public static final double DEFAULT_RHO_MIN
      Default Min Value for the Weight for ADMM iteration.
      See Also:

    • DEFAULT_MAX_RHO_ITERATION

      public static final int DEFAULT_MAX_RHO_ITERATION
      Default Max number of weight changes.
      See Also:

    • DEFAULT_POLISHING

      public static final boolean DEFAULT_POLISHING
      Default Value for enabling polishing the solution.
      See Also:

    • DEFAULT_POLISHING_ITERATION

      public static final int DEFAULT_POLISHING_ITERATION
      Default Value for Iteration of polishing Algorithm.
      See Also:

  • Constructor Details

    • ADMMQPOption

      public ADMMQPOption()
      Simple constructor.

  • Method Details

    • setEps

      public void setEps(double eps)
      Set absolute and Relative Tolerance for convergence.
      Parameters:
      eps - absolute and Relative Tolerance for convergence

    • getEps

      public double getEps()
      Get absolute and Relative Tolerance for convergence.
      Returns:
      absolute and Relative Tolerance for convergence

    • setEpsInfeasible

      public void setEpsInfeasible(double epsInfeasible)
      Set absolute and Relative Tolerance for infeasible criteria.
      Parameters:
      epsInfeasible - absolute and Relative Tolerance for infeasible criteria

    • getEpsInfeasible

      public double getEpsInfeasible()
      Get absolute and Relative Tolerance for infeasible criteria.
      Returns:
      absolute and Relative Tolerance for infeasible criteria

    • setSigma

      public void setSigma(double sigma)
      Set value of regularization term sigma for Karush–Kuhn–Tucker solver.
      Parameters:
      sigma - value of regularization term sigma for Karush–Kuhn–Tucker solver

    • getSigma

      public double getSigma()
      Get value of regularization term sigma for Karush–Kuhn–Tucker solver.
      Returns:
      value of regularization term sigma for Karush–Kuhn–Tucker solver

    • setAlpha

      public void setAlpha(double alpha)
      Set value of alpha filter for ADMM iteration.
      Parameters:
      alpha - value of alpha filter for ADMM iteration

    • getAlpha

      public double getAlpha()
      Get value of alpha filter for ADMM iteration.
      Returns:
      value of alpha filter for ADMM iteration

    • setScaling

      public void setScaling(boolean scaling)
      Set scaling enabling flag.
      Parameters:
      scaling - if true, scaling is enabled

    • isScaling

      public boolean isScaling()
      Check if scaling is enabled.
      Returns:
      true if scaling is enabled

    • setScaleMaxIteration

      public void setScaleMaxIteration(int scaleMaxIteration)
      Set max iteration for the scaling.
      Parameters:
      scaleMaxIteration - max iteration for the scaling

    • getScaleMaxIteration

      public int getScaleMaxIteration()
      Get max iteration for the scaling.
      Returns:
      max iteration for the scaling

    • setUpdateRho

      public void setUpdateRho(boolean updateRho)
      Set weight updating flag.
      Parameters:
      updateRho - if true, weight is updated during iterations

    • updateRho

      public boolean updateRho()
      Check if weight updating is enabled.
      Returns:
      true if weight is updated during iterations

    • setRhoMin

      public void setRhoMin(double rhoMin)
      Set min Value for the Weight for ADMM iteration.
      Parameters:
      rhoMin - min Value for the Weight for ADMM iteration

    • getRhoMin

      public double getRhoMin()
      Get min Value for the Weight for ADMM iteration.
      Returns:
      min Value for the Weight for ADMM iteration

    • setRhoMax

      public void setRhoMax(double rhoMax)
      Set max Value for the Weight for ADMM iteration.
      Parameters:
      rhoMax - max Value for the Weight for ADMM iteration

    • getRhoMax

      public double getRhoMax()
      Get max Value for the Weight for ADMM iteration.
      Returns:
      max Value for the Weight for ADMM iteration

    • setMaxRhoIteration

      public void setMaxRhoIteration(int maxRhoIteration)
      Set max number of weight changes.
      Parameters:
      maxRhoIteration - max number of weight changes

    • getMaxRhoIteration

      public int getMaxRhoIteration()
      Get max number of weight changes.
      Returns:
      max number of weight changes

    • setPolishing

      public void setPolishing(boolean polishing)
      Set polishing enabling flag.
      Parameters:
      polishing - if true, polishing is enabled

    • isPolishing

      public boolean isPolishing()
      Check if polishing is enabled.
      Returns:
      true if polishing is enabled

    • setPolishingIteration

      public void setPolishingIteration(int polishingIteration)
      Set number of iterations of polishing algorithm.
      Parameters:
      polishingIteration - number of iterations of polishing algorithm

    • getPolishIteration

      public int getPolishIteration()
      Get number of iterations of polishing algorithm.
      Returns:
      number of iterations of polishing algorithm