Package org.hipparchus.optim.nonlinear.scalar.gradient

Class NonLinearConjugateGradientOptimizer

java.lang.Object

org.hipparchus.optim.BaseOptimizer<P>

org.hipparchus.optim.BaseMultivariateOptimizer<PointValuePair>

org.hipparchus.optim.nonlinear.scalar.MultivariateOptimizer

org.hipparchus.optim.nonlinear.scalar.GradientMultivariateOptimizer

org.hipparchus.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer

public class NonLinearConjugateGradientOptimizer
extends GradientMultivariateOptimizer

Non-linear conjugate gradient optimizer.
This class supports both the Fletcher-Reeves and the Polak-Ribière update formulas for the conjugate search directions. It also supports optional preconditioning.
Constraints are not supported: the call to optimize will throw MathRuntimeException if bounds are passed to it.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static enum	NonLinearConjugateGradientOptimizer.Formula	Available choices of update formulas for the updating the parameter that is used to compute the successive conjugate search directions.
static class	NonLinearConjugateGradientOptimizer.IdentityPreconditioner	Default identity preconditioner.

Field Summary

Fields inherited from class org.hipparchus.optim.BaseOptimizer

evaluations, iterations

Constructor Summary

Constructors

Constructor	Description
NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula updateFormula, ConvergenceChecker<PointValuePair> checker)	Constructor with default tolerances for the line search (1e-8) and preconditioner.
NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula updateFormula, ConvergenceChecker<PointValuePair> checker, double relativeTolerance, double absoluteTolerance, double initialBracketingRange)	Constructor with default preconditioner.
NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula updateFormula, ConvergenceChecker<PointValuePair> checker, double relativeTolerance, double absoluteTolerance, double initialBracketingRange, Preconditioner preconditioner)	Simple constructor.

Method Summary

Modifier and Type	Method	Description
protected PointValuePair	doOptimize()	Performs the bulk of the optimization algorithm.
PointValuePair	optimize(OptimizationData... optData)	Stores data and performs the optimization.
protected void	parseOptimizationData(OptimizationData... optData)	Scans the list of (required and optional) optimization data that characterize the problem.

Methods inherited from class org.hipparchus.optim.nonlinear.scalar.GradientMultivariateOptimizer

computeObjectiveGradient

Methods inherited from class org.hipparchus.optim.nonlinear.scalar.MultivariateOptimizer

computeObjectiveValue, getGoalType

Methods inherited from class org.hipparchus.optim.BaseMultivariateOptimizer

getLowerBound, getStartPoint, getUpperBound

Methods inherited from class org.hipparchus.optim.BaseOptimizer

getConvergenceChecker, getEvaluations, getIterations, getMaxEvaluations, getMaxIterations, incrementEvaluationCount, incrementIterationCount, optimize

Methods inherited from class java.lang.Object

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

Constructor Details

NonLinearConjugateGradientOptimizer

public NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula updateFormula,
 ConvergenceChecker<PointValuePair> checker)

Constructor with default tolerances for the line search (1e-8) and preconditioner.

Parameters:

updateFormula - formula to use for updating the β parameter, must be one of NonLinearConjugateGradientOptimizer.Formula.FLETCHER_REEVES or NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE.

checker - Convergence checker.

NonLinearConjugateGradientOptimizer

public NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula updateFormula,
 ConvergenceChecker<PointValuePair> checker,
 double relativeTolerance,
 double absoluteTolerance,
 double initialBracketingRange)

Constructor with default preconditioner.

Parameters:

updateFormula - formula to use for updating the β parameter, must be one of NonLinearConjugateGradientOptimizer.Formula.FLETCHER_REEVES or NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE.

checker - Convergence checker.

relativeTolerance - Relative threshold for line search.

absoluteTolerance - Absolute threshold for line search.

initialBracketingRange - Extent of the initial interval used to find an interval that brackets the optimum in order to perform the line search.

See Also:

• LineSearch(org.hipparchus.optim.nonlinear.scalar.MultivariateOptimizer,double,double,double)

NonLinearConjugateGradientOptimizer

public NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula updateFormula,
 ConvergenceChecker<PointValuePair> checker,
 double relativeTolerance,
 double absoluteTolerance,
 double initialBracketingRange,
 Preconditioner preconditioner)

Simple constructor.

Parameters:

updateFormula - formula to use for updating the β parameter, must be one of NonLinearConjugateGradientOptimizer.Formula.FLETCHER_REEVES or NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE.

checker - Convergence checker.

preconditioner - Preconditioner.

relativeTolerance - Relative threshold for line search.

absoluteTolerance - Absolute threshold for line search.

initialBracketingRange - Extent of the initial interval used to find an interval that brackets the optimum in order to perform the line search.

See Also:

• LineSearch(org.hipparchus.optim.nonlinear.scalar.MultivariateOptimizer,double,double,double)

Method Details

optimize

public PointValuePair optimize(OptimizationData... optData)
                        throws MathIllegalStateException

Stores data and performs the optimization.

The list of parameters is open-ended so that sub-classes can extend it with arguments specific to their concrete implementations.

When the method is called multiple times, instance data is overwritten only when actually present in the list of arguments: when not specified, data set in a previous call is retained (and thus is optional in subsequent calls).

Important note: Subclasses must override BaseOptimizer.parseOptimizationData(OptimizationData[]) if they need to register their own options; but then, they must also call super.parseOptimizationData(optData) within that method.

Overrides:

optimize in class GradientMultivariateOptimizer

Parameters:

optData - Optimization data. In addition to those documented in MultivariateOptimizer, this method will register the following data:

• ObjectiveFunctionGradient

Returns:

a point/value pair that satisfies the convergence criteria.

Throws:

MathIllegalStateException - if the maximal number of evaluations (of the objective function) is exceeded.

doOptimize

protected PointValuePair doOptimize()

Performs the bulk of the optimization algorithm.

Specified by:

doOptimize in class BaseOptimizer<PointValuePair>

Returns:

the point/value pair giving the optimal value of the objective function.

parseOptimizationData

protected void parseOptimizationData(OptimizationData... optData)

Scans the list of (required and optional) optimization data that characterize the problem.

Overrides:

parseOptimizationData in class GradientMultivariateOptimizer

Parameters:

optData - Optimization data. The following data will be looked for:

• ObjectiveFunctionGradient