org.apache.commons.math.optimization

## Class MultiStartDifferentiableMultivariateVectorialOptimizer

- java.lang.Object
- - org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer

All Implemented Interfaces:
  DifferentiableMultivariateVectorialOptimizer

    public class MultiStartDifferentiableMultivariateVectorialOptimizer
    extends Object
    implements DifferentiableMultivariateVectorialOptimizer

Special implementation of the `DifferentiableMultivariateVectorialOptimizer` interface adding multi-start features to an existing optimizer.

This class wraps a classical optimizer to use it several times in turn with different starting points in order to avoid being trapped into a local extremum when looking for a global one.

Since:
  2.0
Version:
  $Revision: 1073158 $ $Date: 2011-02-21 22:46:52 +0100 (lun. 21 févr. 2011) $

### Field Summary

Fields
`private RandomVectorGenerator` `generator` Random generator for multi-start.
`private int` `maxEvaluations` Maximal number of evaluations allowed.
`private int` `maxIterations` Maximal number of iterations allowed.
`private VectorialPointValuePair[]` `optima` Found optima.
`private DifferentiableMultivariateVectorialOptimizer` `optimizer` Underlying classical optimizer.
`private static long` `serialVersionUID` Serializable version identifier.
`private int` `starts` Number of starts to go.
`private int` `totalEvaluations` Number of evaluations already performed for all starts.
`private int` `totalIterations` Number of iterations already performed for all starts.
`private int` `totalJacobianEvaluations` Number of jacobian evaluations already performed for all starts.

### Constructor Summary

Constructors
Constructor and Description
`MultiStartDifferentiableMultivariateVectorialOptimizer(DifferentiableMultivariateVectorialOptimizer optimizer, int starts, RandomVectorGenerator generator)` Create a multi-start optimizer from a single-start optimizer

### Method Summary

Methods
`VectorialConvergenceChecker` `getConvergenceChecker()` Get the convergence checker.
`int` `getEvaluations()` Get the number of evaluations of the objective function.
`int` `getIterations()` Get the number of iterations realized by the algorithm.
`int` `getJacobianEvaluations()` Get the number of evaluations of the objective function jacobian .
`int` `getMaxEvaluations()` Get the maximal number of functions evaluations.
`int` `getMaxIterations()` Get the maximal number of iterations of the algorithm.
`VectorialPointValuePair[]` `getOptima()` Get all the optima found during the last call to `optimize`.
`VectorialPointValuePair` `optimize(DifferentiableMultivariateVectorialFunction f, double[] target, double[] weights, double[] startPoint)` Optimizes an objective function.
`void` `setConvergenceChecker(VectorialConvergenceChecker checker)` Set the convergence checker.
`void` `setMaxEvaluations(int maxEvaluations)` Set the maximal number of functions evaluations.
`void` `setMaxIterations(int maxIterations)` Set the maximal number of iterations of the algorithm.

### Methods inherited from class java.lang.Object

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

### Field Detail

#### serialVersionUID

    private static final long serialVersionUID

Serializable version identifier.

See Also:
  Constant Field Values

#### optimizer

    private final DifferentiableMultivariateVectorialOptimizer optimizer

Underlying classical optimizer.

#### maxIterations

    private int maxIterations

Maximal number of iterations allowed.

#### totalIterations

    private int totalIterations

Number of iterations already performed for all starts.

#### maxEvaluations

    private int maxEvaluations

Maximal number of evaluations allowed.

#### totalEvaluations

    private int totalEvaluations

Number of evaluations already performed for all starts.

#### totalJacobianEvaluations

    private int totalJacobianEvaluations

Number of jacobian evaluations already performed for all starts.

#### starts

    private int starts

Number of starts to go.

#### generator

    private RandomVectorGenerator generator

Random generator for multi-start.

#### optima

    private VectorialPointValuePair[] optima

Found optima.

### Constructor Detail

#### MultiStartDifferentiableMultivariateVectorialOptimizer

    public MultiStartDifferentiableMultivariateVectorialOptimizer(DifferentiableMultivariateVectorialOptimizer optimizer,
                                                          int starts,
                                                          RandomVectorGenerator generator)

Create a multi-start optimizer from a single-start optimizer

Parameters:
  `optimizer` - single-start optimizer to wrap
  `starts` - number of starts to perform (including the first one), multi-start is disabled if value is less than or equal to 1
  `generator` - random vector generator to use for restarts

### Method Detail

#### getOptima

    public VectorialPointValuePair[] getOptima()
                                        throws IllegalStateException

Get all the optima found during the last call to `optimize`.

The optimizer stores all the optima found during a set of restarts. The `optimize` method returns the best point only. This method returns all the points found at the end of each starts, including the best one already returned by the `optimize` method.

The returned array as one element for each start as specified in the constructor. It is ordered with the results from the runs that did converge first, sorted from best to worst objective value (i.e in ascending order if minimizing and in descending order if maximizing), followed by and null elements corresponding to the runs that did not converge. This means all elements will be null if the `optimize` method did throw a `ConvergenceException`). This also means that if the first element is non null, it is the best point found across all starts.

Returns:
  array containing the optima
Throws:
  `IllegalStateException` - if `optimize` has not been called

#### setMaxIterations

    public void setMaxIterations(int maxIterations)

Set the maximal number of iterations of the algorithm.

Specified by:
  `setMaxIterations` in interface `DifferentiableMultivariateVectorialOptimizer`
Parameters:
  `maxIterations` - maximal number of function calls .

#### getMaxIterations

    public int getMaxIterations()

Get the maximal number of iterations of the algorithm.

Specified by:
  `getMaxIterations` in interface `DifferentiableMultivariateVectorialOptimizer`
Returns:
  maximal number of iterations

#### getIterations

    public int getIterations()

Get the number of iterations realized by the algorithm.

Specified by:
  `getIterations` in interface `DifferentiableMultivariateVectorialOptimizer`
Returns:
  number of iterations

#### setMaxEvaluations

    public void setMaxEvaluations(int maxEvaluations)

Set the maximal number of functions evaluations.

Specified by:
  `setMaxEvaluations` in interface `DifferentiableMultivariateVectorialOptimizer`
Parameters:
  `maxEvaluations` - maximal number of function evaluations

#### getMaxEvaluations

    public int getMaxEvaluations()

Get the maximal number of functions evaluations.

Specified by:
  `getMaxEvaluations` in interface `DifferentiableMultivariateVectorialOptimizer`
Returns:
  maximal number of functions evaluations

#### getEvaluations

    public int getEvaluations()

Get the number of evaluations of the objective function.

The number of evaluation correspond to the last call to the `optimize` method. It is 0 if the method has not been called yet.

Specified by:
  `getEvaluations` in interface `DifferentiableMultivariateVectorialOptimizer`
Returns:
  number of evaluations of the objective function

#### getJacobianEvaluations

    public int getJacobianEvaluations()

Get the number of evaluations of the objective function jacobian .

The number of evaluation correspond to the last call to the `optimize` method. It is 0 if the method has not been called yet.

Specified by:
  `getJacobianEvaluations` in interface `DifferentiableMultivariateVectorialOptimizer`
Returns:
  number of evaluations of the objective function jacobian

#### setConvergenceChecker

    public void setConvergenceChecker(VectorialConvergenceChecker checker)

Set the convergence checker.

Specified by:
  `setConvergenceChecker` in interface `DifferentiableMultivariateVectorialOptimizer`
Parameters:
  `checker` - object to use to check for convergence

#### getConvergenceChecker

    public VectorialConvergenceChecker getConvergenceChecker()

Get the convergence checker.

Specified by:
  `getConvergenceChecker` in interface `DifferentiableMultivariateVectorialOptimizer`
Returns:
  object used to check for convergence

#### optimize

    public VectorialPointValuePair optimize(DifferentiableMultivariateVectorialFunction f,
                                   double[] target,
                                   double[] weights,
                                   double[] startPoint)
                                     throws FunctionEvaluationException,
                                            OptimizationException,
                                            IllegalArgumentException

Optimizes an objective function.

Optimization is considered to be a weighted least-squares minimization. The cost function to be minimized is ∑weighti(objectivei-targeti)2

Specified by:
  `optimize` in interface `DifferentiableMultivariateVectorialOptimizer`
Parameters:
  `f` - objective function
  `target` - target value for the objective functions at optimum
  `weights` - weight for the least squares cost computation
  `startPoint` - the start point for optimization
Returns:
  the point/value pair giving the optimal value for objective function
Throws:
  `FunctionEvaluationException` - if the objective function throws one during the search
  `OptimizationException` - if the algorithm failed to converge
  `IllegalArgumentException` - if the start point dimension is wrong