Package org.apache.commons.math4.legacy.optim.nonlinear.scalar

Class MultivariateOptimizer

java.lang.Object

org.apache.commons.math4.legacy.optim.BaseOptimizer<PAIR>

org.apache.commons.math4.legacy.optim.BaseMultivariateOptimizer<PointValuePair>

org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultivariateOptimizer

Direct Known Subclasses:

BOBYQAOptimizer, CMAESOptimizer, GradientMultivariateOptimizer, LinearOptimizer, PowellOptimizer, SimplexOptimizer

public abstract class MultivariateOptimizer
extends BaseMultivariateOptimizer<PointValuePair>

Base class for a multivariate scalar function optimizer.

Since:

3.1

Constructor Summary

Constructors

Modifier	Constructor	Description
protected	MultivariateOptimizer(ConvergenceChecker<PointValuePair> checker)

Method Summary

Modifier and Type	Method	Description
double	computeObjectiveValue(double[] params)	Deprecated. Use getObjectiveFunction() instead.
protected void	createLineSearch()	Intantiate the line search implementation.
protected GoalType	getGoalType()
protected MultivariateFunction	getObjectiveFunction()
protected UnivariatePointValuePair	lineSearch(double[] startPoint, double[] direction)	Finds the number alpha that optimizes f(startPoint + alpha * direction).
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.apache.commons.math4.legacy.optim.BaseMultivariateOptimizer

getLowerBound, getStartPoint, getUpperBound

Methods inherited from class org.apache.commons.math4.legacy.optim.BaseOptimizer

doOptimize, getAbsoluteTolerance, getConvergenceChecker, getEvaluations, getIterations, getMaxEvaluations, getMaxIterations, getRelativeTolerance, incrementEvaluationCount, incrementIterationCount, optimize

Methods inherited from class java.lang.Object

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

Constructor Detail

MultivariateOptimizer

protected MultivariateOptimizer(ConvergenceChecker<PointValuePair> checker)

Parameters:

checker - Convergence checker.

Method Detail

optimize

public PointValuePair optimize(OptimizationData... optData)

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 BaseMultivariateOptimizer<PointValuePair>

Parameters:

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

• ObjectiveFunction
• GoalType
• LineSearchTolerance

Returns:

a point/value pair that satisfies the convergence criteria.

Throws:

TooManyEvaluationsException - if the maximal number of evaluations is exceeded.

parseOptimizationData

protected void parseOptimizationData(OptimizationData... optData)

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

Overrides:

parseOptimizationData in class BaseMultivariateOptimizer<PointValuePair>

Parameters:

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

• ObjectiveFunction
• GoalType
• LineSearchTolerance

createLineSearch

protected void createLineSearch()

Intantiate the line search implementation.

lineSearch

protected UnivariatePointValuePair lineSearch(double[] startPoint,
                                              double[] direction)

Finds the number alpha that optimizes f(startPoint + alpha * direction).

Parameters:

startPoint - Starting point.

direction - Search direction.

Returns:

the optimum.

Throws:

TooManyEvaluationsException - if the number of evaluations is exceeded.

getGoalType

protected GoalType getGoalType()

Returns:

the optimization type.

getObjectiveFunction

protected MultivariateFunction getObjectiveFunction()

Returns:

a wrapper that delegates to the user-supplied function, and counts the number of evaluations.

computeObjectiveValue

@Deprecated
public double computeObjectiveValue(double[] params)

Deprecated.

Use getObjectiveFunction() instead.

Computes the objective function value. This method must be called by subclasses to enforce the evaluation counter limit.

Parameters:

params - Point at which the objective function must be evaluated.

Returns:

the objective function value at the specified point.

Throws:

TooManyEvaluationsException - if the maximal number of evaluations is exceeded.