Represents a line search using a backtracking algorithm.
| Name | Description |
---|
 | ConvergenceTests |
Gets the collection of convergence tests for the algorithm.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.) |
 | DerivativeOfObjectiveFunction |
Gets or sets the derivative of the objective function.
(Inherited from OneDimensionalOptimizer.) |
 | DescentFactor |
Gets or sets the factor in the sufficient descent condition.
|
 | EstimatedError |
Gets a value indicating the size of the absolute
error of the result.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.) |
 | EvaluationsNeeded |
Gets the number of evaluations needed to execute the algorithm.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.) |
 | Extremum |
Gets the approximation to the extremum after the algorithm has run.
(Inherited from OneDimensionalOptimizer.) |
 | ExtremumType |
Gets or sets the type of extremum.
(Inherited from OneDimensionalOptimizer.) |
 | HasSharedDegreeOfParallelism |
Indicates whether the degree of parallelism is a property that is shared
across instances.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.) |
 | IsBracketValid |
Gets whether the algorithm's current bracket is valid.
(Inherited from OneDimensionalOptimizer.) |
 | IterationsNeeded |
Gets the number of iterations needed by the
algorithm to reach the desired accuracy.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.) |
 | MaxContractionFactor |
Gets or sets the largest allowed contraction factor between steps in the backtracking procedure.
|
 | MaxDegreeOfParallelism |
Gets or sets the maximum degree of parallelism enabled by this instance.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.) |
 | MaxEvaluations |
Gets or sets the maximum number of evaluations during the calculation.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.) |
 | MaxIterations | Gets or sets the maximum number of iterations
to use when approximating the roots of the target
function.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.) |
 | MaxStepLength |
Gets or sets the largest allowed step length.
|
 | MinContractionFactor |
Gets or sets the smallest allowed contraction factor between steps in the backtracking procedure.
|
 | MinIterations |
Gets or sets the minimum iterations that have to be performed.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.) |
 | ObjectiveFunction |
Gets or sets the objective function.
(Inherited from OneDimensionalOptimizer.) |
 | ObjectiveFunctionWithDerivative |
Gets or sets a function that computes the value of the objective function
and its derivative.
(Inherited from OneDimensionalOptimizer.) |
 | ParallelOptions |
Gets or sets the configuration for the parallel behavior of the algorithm.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.) |
 | Result |
Gets the result of an algorithm after it has executed.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.) |
 | SolutionReport |
Gets the result of an algorithm after it has executed.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.) |
 | SolutionTest |
Gets the convergence test that uses the solution of the optimization.
(Inherited from OneDimensionalOptimizer.) |
 | Status | (Inherited from ManagedIterativeAlgorithmT, TError, TReport.) |
 | SymbolicObjectiveFunction |
Gets or sets the objective function.
(Inherited from OneDimensionalOptimizer.) |
 | ThrowExceptionOnFailure |
Gets or sets a value indicating whether to throw an
exception when the algorithm fails to converge.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.) |
 | ValueAtExtremum |
Gets the value of the objective function at the approximation to the extremum after the algorithm has run.
(Inherited from OneDimensionalOptimizer.) |
| Name | Description |
---|
 | Equals | Determines whether the specified object is equal to the current object. (Inherited from Object.) |
 | FindBracket |
Finds an interval that brackets the extremum, starting from the interval [0,1].
(Inherited from OneDimensionalOptimizer.) |
 | FindBracket(Double) |
Finds an interval that brackets the extremum, starting from an interval of unit width centered around the specified point.
(Inherited from OneDimensionalOptimizer.) |
 | FindBracket(Double, Double) |
Finds an interval that brackets the extremum, starting from an interval with the specified bounds.
(Inherited from OneDimensionalOptimizer.) |
 | FindBracket(Double, Double, Double) |
Finds an interval that brackets the extremum, starting from an interval with the specified bounds and
interior point.
(Inherited from OneDimensionalOptimizer.) |
 | FindExtremum |
Searches for an extremum.
(Inherited from OneDimensionalOptimizer.) |
 | FindMaximum(FuncDouble, Double, Double) |
Computes a maximum of the specified function.
(Inherited from OneDimensionalOptimizer.) |
 | FindMaximum(FuncDouble, Double, Double, Double) |
Computes a maximum of the specified function.
(Inherited from OneDimensionalOptimizer.) |
 | FindMinimum(FuncDouble, Double, Double) |
Computes a minimum of the specified function.
(Inherited from OneDimensionalOptimizer.) |
 | FindMinimum(FuncDouble, Double, Double, Double) |
Computes a minimum of the specified function.
(Inherited from OneDimensionalOptimizer.) |
 | GetHashCode | Serves as the default hash function. (Inherited from Object.) |
 | GetType | Gets the Type of the current instance. (Inherited from Object.) |
 | ToString | Returns a string that represents the current object. (Inherited from Object.) |
The backtracking algorithm is the line search method of choice for most
applications, particularly when the gradient of the objective function is relatively expensive.
The algorithm uses a custom termination criterion based on the Wolfe conditions.
These conditions guarantee convergence of quasi-Newton algorithms
in most situations.
The algorithm uses the Armijo conditions as termination criteria.
The parameter of the Armijo conditions can be set or retrieved through the
DescentFactor property, while the rate of backtracking
can be controlled through the MinContractionFactor and
MaxContractionFactor properties.