Blurb:: NLPQL Sequential Quadratic Program

Description::
NLPQL implementation of sequential quadratic programming.  The
particular SQP implementation in \c nlpql_sqp uses a variant with
distributed and non-monotone line search.  Thus, this variant is
designed to be more robust in the presence of inaccurate or noisy
gradients common in many engineering applications.

<em>NLPQL requires a separate software license and therefore may not
be available in all versions of Dakota.  CONMIN or OPT++ methods may
be suitable alternatives.</em>

The method independent controls for maximum iterations and output
verbosity are mapped to NLPQL controls MAXIT and IPRINT, respectively.
The maximum number of function evaluations is enforced within the
NLPQLPOptimizer class.

<b>Expected HDF5 Output</b> 

If Dakota was built with HDF5 support and run with the 
\ref environment-results_output-hdf5 keyword, this method 
writes the following results to HDF5: 

- \ref hdf5_results-best_params 
- \ref hdf5_results-best_obj_fncs (when \ref responses-objective_functions) are specified) 
- \ref hdf5_results-best_constraints 
- \ref hdf5_results-calibration (when \ref responses-calibration_terms are specified) 

Topics::	package_nlpql, sequential_quadratic_programming, local_optimization_methods
Examples::
Theory::
Faq::
See_Also::	
