Blurb:: Sequential Quadratic Program for nonlinear least squares

Description::
NLSSOL supports unconstrained, bound-constrained, and
generally-constrained least-squares calibration problems. It exploits
the structure of a least squares objective function through the
periodic use of Gauss-Newton Hessian approximations to accelerate the
SQP algorithm.

<em>NLSSOL requires a separate software license and therefore may not
be available in all versions of Dakota.  \ref method-nl2sol or \ref method-optpp_g_newton may be suitable alternatives.</em>


<b> Stopping Criteria </b>

The method independent controls for \c max_iterations and \c
max_function_evaluations limit the number of major SQP iterations and
the number of function evaluations that can be performed during an
NPSOL optimization. The \c convergence_tolerance control defines
NPSOL's internal optimality tolerance which is used in evaluating if
an iterate satisfies the first-order Kuhn-Tucker conditions for a
minimum. The magnitude of \c convergence_tolerance approximately
specifies the number of significant digits of accuracy desired in the
final objective function (e.g., \c convergence_tolerance = \c 1.e-6
will result in approximately six digits of accuracy in the final
objective function). The \c constraint_tolerance control defines how
tightly the constraint functions are satisfied at convergence. The
default value is dependent upon the machine precision of the platform
in use, but is typically on the order of \c 1.e-8 for double precision
computations. Extremely small values for \c constraint_tolerance may
not be attainable. 

<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_constraints 
- \ref hdf5_results-calibration (when \ref responses-calibration_terms are specified) 
- \ref hdf5_results-lsq_confidence_intervals (when 
\ref responses-calibration_terms-calibration_data-num_experiments equals 1) 

Topics::	sequential_quadratic_programming, nonlinear_least_squares 
Examples::
Theory::
Faq::
See_Also::	method-npsol_sqp, method-nl2sol, method-optpp_g_newton, responses-calibration_terms-field_calibration_terms
