IGLib  1.7.2
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IG.Num.OptUnconstrained.ExampleRosenbrock Class Reference

The Rosenbrock's unconstrained optimization problem (2D). More...

+ Inheritance diagram for IG.Num.OptUnconstrained.ExampleRosenbrock:
+ Collaboration diagram for IG.Num.OptUnconstrained.ExampleRosenbrock:

Public Member Functions

override void Analyse (IAnalysisResults analysisData)
 Performs the direct analysis, i.e. calculation of the response functions of the optimization problem. More...
 

Protected Attributes

ScalarFunctionBase _objectiveFunction
 
IVector _grad = null
 
IMatrix _hess = null
 
- Protected Attributes inherited from IG.Num.AnalysisBase
int _numParameters = -1
 
int _numObjectives = -1
 
int _numConstraints = -1
 
int _numEqualityConstraints = -1
 

Properties

override int NumParameters [get, set]
 Number of parameters. More...
 
override int NumObjectives [get, set]
 Number of objectives. More...
 
override int NumConstraints [get, set]
 Number of constraints. More...
 
virtual ScalarFunctionBase ObjectiveFunction [get, protected set]
 The scalar function object that can perform evaluation of the Rosenbrock function and eventually its derivatives. More...
 
- Properties inherited from IG.Num.AnalysisBase
object Lock [get]
 
virtual int NumParameters [get, set]
 Number of parameters. More...
 
virtual int NumObjectives [get, set]
 Number of objective functions (normally 1 for this type, but can be 0). More...
 
virtual int NumConstraints [get, set]
 Number of constraints. More...
 
virtual int NumEqualityConstraints [get, set]
 Number of equality constraints. More...
 
- Properties inherited from IG.Num.IAnalysis
int NumParameters [get, set]
 Number of parameters. More...
 
int NumObjectives [get, set]
 Number of objective functions (normally 1 for this type, but can be 0). More...
 
int NumConstraints [get, set]
 Number of constraints. More...
 
int NumEqualityConstraints [get, set]
 Number of equality constraints. More...
 
- Properties inherited from IG.Lib.ILockable
object Lock [get]
 

Detailed Description

The Rosenbrock's unconstrained optimization problem (2D).

min f(x) = f(x,y) = (1-x)^2 + 100 * (y-x^2)^2

Unique local minimum:

x = 1, y = 1, f(x, y) = 0.

This function is often used for testing optimization algorithms due to the banana - like shape of its contours.

On Wikipedia: http://en.wikipedia.org/wiki/Rosenbrock_function

Member Function Documentation

Member Data Documentation

ScalarFunctionBase IG.Num.OptUnconstrained.ExampleRosenbrock._objectiveFunction
protected
IVector IG.Num.OptUnconstrained.ExampleRosenbrock._grad = null
protected
IMatrix IG.Num.OptUnconstrained.ExampleRosenbrock._hess = null
protected

Property Documentation

override int IG.Num.OptUnconstrained.ExampleRosenbrock.NumParameters
getset

Number of parameters.

override int IG.Num.OptUnconstrained.ExampleRosenbrock.NumObjectives
getset

Number of objectives.

override int IG.Num.OptUnconstrained.ExampleRosenbrock.NumConstraints
getset

Number of constraints.

virtual ScalarFunctionBase IG.Num.OptUnconstrained.ExampleRosenbrock.ObjectiveFunction
getprotected set

The scalar function object that can perform evaluation of the Rosenbrock function and eventually its derivatives.


The documentation for this class was generated from the following file: