org.apache.commons.math3.optim.nonlinear.scalar

## Class MultivariateOptimizer

- 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

- 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
  Version:
    $Id: MultivariateOptimizer.java 1572988 2014-02-28 16:23:26Z erans $

- - ### Field Summary

    - ### Fields inherited from class org.apache.commons.math3.optim.BaseOptimizer

      `evaluations, iterations`

  - ### Constructor Summary

    Constructors
    Modifier | Constructor and Description
    --- | ---
    `protected` | `MultivariateOptimizer(ConvergenceChecker<PointValuePair> checker)`

  - ### Method Summary

    Methods
    Modifier and Type | Method and Description
    --- | ---
    `double` | `computeObjectiveValue(double[] params)` Computes the objective function value.
    `GoalType` | `getGoalType()`
    `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.math3.optim.BaseMultivariateOptimizer

      `getLowerBound, getStartPoint, getUpperBound`

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

      `doOptimize, 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 Detail

    - #### MultivariateOptimizer

          protected MultivariateOptimizer(ConvergenceChecker<PointValuePair> checker)

      Parameters:
        `checker` - Convergence checker.

  - ### 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).

      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`
      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`

    - #### getGoalType

          public GoalType getGoalType()

      Returns:
        the optimization type.

    - #### computeObjectiveValue

          public double computeObjectiveValue(double[] params)

      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.

Copyright © 2003–2014 The Apache Software Foundation. All rights reserved.