NPSOLTraits Class Reference

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

Inheritance diagram for NPSOLTraits:

Public Member Functions
	NPSOLTraits ()
	default constructor
virtual	~NPSOLTraits ()
	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.
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 LINEAR_INEQUALITY_FORMAT	linear_inequality_format ()
	Return the format used for linear inequality constraints.
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 NPSOL optimization library.

The NPSOLOptimizer class provides a wrapper for NPSOL, a Fortran 77 sequential quadratic programming library from Stanford University marketed by Stanford Business Associates. It uses a function pointer approach for which passed functions must be either global functions or static member functions. Any attribute used within static member functions must be either local to that function or accessed through a static pointer.

The user input mappings are as follows: max_function_evaluations is implemented directly in NPSOLOptimizer's evaluator functions since there is no NPSOL parameter equivalent, and max_iterations, convergence_tolerance, output verbosity, verify_level, function_precision, and linesearch_tolerance are mapped into NPSOL's "Major Iteration Limit", "Optimality Tolerance", "Major Print Level" (verbose: Major Print Level = 20; quiet: Major Print Level = 10), "Verify Level", "Function Precision", and "Linesearch Tolerance" parameters, respectively, using NPSOL's npoptn() subroutine (as wrapped by npoptn2() from the sol_optn_wrapper.f file). Refer to [Gill, P.E., Murray, W., Saunders, M.A., and Wright, M.H., 1986] for information on NPSOL's optional input parameters and the npoptn() subroutine.

A version of TraitsBase specialized for NPSOL optimizers

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

• NPSOLOptimizer.hpp