org.apache.commons.math3.optim.nonlinear.scalar.gradient
Class NonLinearConjugateGradientOptimizer

java.lang.Object
  org.apache.commons.math3.optim.BaseOptimizer<PAIR>
      org.apache.commons.math3.optim.BaseMultivariateOptimizer<PointValuePair>
          org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer
              org.apache.commons.math3.optim.nonlinear.scalar.GradientMultivariateOptimizer
                  org.apache.commons.math3.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.

Since:

2.0

Version:

$Id: NonLinearConjugateGradientOptimizer.java 7721 2013-02-14 14:07:13Z CardosoP $

Nested Class Summary

static class	NonLinearConjugateGradientOptimizer.BracketingStep The initial step is a factor with respect to the search direction (which itself is roughly related to the gradient of the function).
static class	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.apache.commons.math3.optim.BaseOptimizer

evaluations, iterations

Constructor Summary

NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula updateFormula, ConvergenceChecker<PointValuePair> checker)
Constructor with default line search solver and preconditioner.

NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula updateFormula, ConvergenceChecker<PointValuePair> checker, UnivariateSolver lineSearchSolver)
Constructor with default preconditioner.

NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula updateFormula, ConvergenceChecker<PointValuePair> checker, UnivariateSolver lineSearchSolver, Preconditioner preconditioner)

Method Summary

protected PointValuePair	doOptimize() Performs the bulk of the optimization algorithm.
PointValuePair	optimize(OptimizationData... optData) Stores data and performs the optimization.

Methods inherited from class org.apache.commons.math3.optim.nonlinear.scalar.GradientMultivariateOptimizer

computeObjectiveGradient

Methods inherited from class org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer

computeObjectiveValue, getGoalType

Methods inherited from class org.apache.commons.math3.optim.BaseMultivariateOptimizer

getLowerBound, getStartPoint, getUpperBound

Methods inherited from class org.apache.commons.math3.optim.BaseOptimizer

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

Methods inherited from class java.lang.Object

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

Constructor Detail

NonLinearConjugateGradientOptimizer

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

Constructor with default line search solver 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,
                                           UnivariateSolver lineSearchSolver)

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.

lineSearchSolver - Solver to use during line search.

NonLinearConjugateGradientOptimizer

public NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula updateFormula,
                                           ConvergenceChecker<PointValuePair> checker,
                                           UnivariateSolver lineSearchSolver,
                                           Preconditioner 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.

lineSearchSolver - Solver to use during line search.

preconditioner - Preconditioner.

Method Detail

optimize

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

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).

Overrides:

optimize in class GradientMultivariateOptimizer

Parameters:

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

• MaxEval
• InitialGuess
• SimpleBounds
• GoalType
• ObjectiveFunction
• ObjectiveFunctionGradient
• NonLinearConjugateGradientOptimizer.BracketingStep

Returns:

a point/value pair that satifies the convergence criteria.

Throws:

TooManyEvaluationsException - 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.