See: Description
Interface  Description 

BaseMultivariateOptimizer<FUNC extends MultivariateFunction> 
This interface is mainly intended to enforce the internal coherence of
CommonsFastMath.

BaseMultivariateSimpleBoundsOptimizer<FUNC extends MultivariateFunction> 
This interface is mainly intended to enforce the internal coherence of
CommonsFastMath.

BaseMultivariateVectorOptimizer<FUNC extends MultivariateVectorFunction> 
This interface is mainly intended to enforce the internal coherence of
CommonsMath.

BaseOptimizer<PAIR> 
This interface is mainly intended to enforce the internal coherence of
CommonsMath.

ConvergenceChecker<PAIR> 
This interface specifies how to check if an optimization algorithm has
converged.

DifferentiableMultivariateOptimizer 
This interface represents an optimization algorithm for
scalar differentiable objective
functions . 
DifferentiableMultivariateVectorOptimizer 
This interface represents an optimization algorithm for
vectorial differentiable
objective functions . 
MultivariateOptimizer 
This interface represents an optimization algorithm for
scalar objective functions . 
Class  Description 

AbstractConvergenceChecker<PAIR> 
Base class for all convergence checker implementations.

BaseMultivariateMultiStartOptimizer<FUNC extends MultivariateFunction> 
Base class for all implementations of a multistart optimizer.

BaseMultivariateVectorMultiStartOptimizer<FUNC extends MultivariateVectorFunction> 
Base class for all implementations of a multistart optimizer.

DifferentiableMultivariateMultiStartOptimizer 
Special implementation of the
DifferentiableMultivariateOptimizer
interface adding multistart features to an existing optimizer. 
DifferentiableMultivariateVectorMultiStartOptimizer 
Special implementation of the
DifferentiableMultivariateVectorOptimizer
interface addind multistart features to an existing optimizer. 
LeastSquaresConverter 
This class converts
vectorial
objective functions to scalar objective functions
when the goal is to minimize them. 
MultivariateMultiStartOptimizer 
Special implementation of the
MultivariateOptimizer interface adding
multistart features to an existing optimizer. 
PointValuePair 
This class holds a point and the value of an objective function at
that point.

PointVectorValuePair 
This class holds a point and the vectorial value of an objective function at
that point.

SimplePointChecker<PAIR extends Pair<double[],? extends Object>> 
Simple implementation of the
ConvergenceChecker interface using
only point coordinates. 
SimpleValueChecker 
Simple implementation of the
ConvergenceChecker interface using
only objective function values. 
SimpleVectorValueChecker 
Simple implementation of the
ConvergenceChecker interface using
only objective function values. 
Enum  Description 

GoalType 
Goal type for an optimization problem.

This package provides common interfaces for the optimization algorithms
provided in subpackages. The main interfaces defines optimizers and convergence
checkers. The functions that are optimized by the algorithms provided by this
package and its subpackages are a subset of the one defined in the analysis
package, namely the real and vector valued functions. These functions are called
objective function here. When the goal is to minimize, the functions are often called
cost function, this name is not used in this package.
Optimizers are the algorithms that will either minimize or maximize, the objective function by changing its input variables set until an optimal set is found. There are only four interfaces defining the common behavior of optimizers, one for each supported type of objective function:
UnivariateOptimizer
for univariate real functions
MultivariateOptimizer
for multivariate real functions
DifferentiableMultivariateOptimizer
for differentiable multivariate real functions
DifferentiableMultivariateVectorOptimizer
for differentiable multivariate vectorial functions
Despite there are only four types of supported optimizers, it is possible to optimize a
transform a nondifferentiable multivariate vectorial function
by converting it to a nondifferentiable multivariate
real function
thanks to the LeastSquaresConverter
helper class.
The transformed function can be optimized using any implementation of the MultivariateOptimizer
interface.
For each of the four types of supported optimizers, there is a special implementation which wraps a classical optimizer in order to add it a multistart feature. This feature call the underlying optimizer several times in sequence with different starting points and returns the best optimum found or all optima if desired. This is a classical way to prevent being trapped into a local extremum when looking for a global one.
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