DOTTraits Class Reference

Wrapper class for the DOT optimization library. More...

Inheritance diagram for DOTTraits:

Public Member Functions
	DOTTraits ()
	default constructor
virtual	~DOTTraits ()
	destructor
virtual bool	is_derived ()
	A temporary query used in the refactor.
bool	supports_continuous_variables ()
	Return the flag indicating whether method supports continuous variables.
bool	supports_linear_equality ()
	Return the flag indicating whether method supports linear equalities.
bool	supports_linear_inequality ()
	Return the flag indicating whether method supports linear inequalities.
LINEAR_INEQUALITY_FORMAT	linear_inequality_format ()
	Return the format used for linear inequality constraints.
bool	supports_nonlinear_equality ()
	Return the flag indicating whether method supports nonlinear equalities.
bool	supports_nonlinear_inequality ()
	Return the flag indicating whether method supports nonlinear inequalities.
NONLINEAR_INEQUALITY_FORMAT	nonlinear_inequality_format ()
	Return the format used for nonlinear inequality constraints.
Public Member Functions inherited from TraitsBase
	TraitsBase ()
	default constructor
virtual	~TraitsBase ()
	destructor
virtual bool	requires_bounds ()
	Return the flag indicating whether method requires bounds.
virtual NONLINEAR_EQUALITY_FORMAT	nonlinear_equality_format ()
	Return the format used for nonlinear equality constraints.
virtual bool	expects_nonlinear_inequalities_first ()
	Return the flag indicating whether method expects nonlinear inequality constraints followed by nonlinear equality constraints.
virtual bool	supports_scaling ()
	Return the flag indicating whether method supports parameter scaling.
virtual bool	supports_least_squares ()
	Return the flag indicating whether method supports least squares.
virtual bool	supports_multiobjectives ()
	Return flag indicating whether method supports multiobjective optimization.
virtual bool	supports_discrete_variables ()
	Return the flag indicating whether method supports continuous variables.
virtual bool	provides_best_objective ()
	Return the flag indicating whether method provides best objective result.
virtual bool	provides_best_parameters ()
	Return the flag indicating whether method provides best parameters result.
virtual bool	provides_best_constraint ()
	Return the flag indicating whether method provides best constraint result.
virtual bool	provides_final_gradient ()
	Return the flag indicating whether method provides final gradient result.
virtual bool	provides_final_hessian ()
	Return the flag indicating whether method provides final hessian result.

Detailed Description

Wrapper class for the DOT optimization library.

The DOTOptimizer class provides a wrapper for DOT, a commercial Fortran 77 optimization library from Vanderplaats Research and Development. It uses a reverse communication mode, which avoids the static member function issues that arise with function pointer designs (see NPSOLOptimizer and SNLLOptimizer).

The user input mappings are as follows: max_iterations is mapped into DOT's ITMAX parameter within its IPRM array, max_function_evaluations is implemented directly in the core_run() loop since there is no DOT parameter equivalent, convergence_tolerance is mapped into DOT's DELOBJ parameter (the relative convergence tolerance) within its RPRM array, output verbosity is mapped into DOT's IPRINT parameter within its function call parameter list (verbose: IPRINT = 7; quiet: IPRINT = 3), and optimization_type is mapped into DOT's MINMAX parameter within its function call parameter list. Refer to [Vanderplaats Research and Development, 1995] for information on IPRM, RPRM, and the DOT function call parameter list.

A version of TraitsBase specialized for DOT optimizers

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

• DOTOptimizer.hpp