Dakota Reference Manual  Version 6.12
Explore and Predict with Confidence
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NLPQL Sequential Quadratic Program


This keyword is related to the topics:


Alias: none

Argument(s): none

Child Keywords:

Required/Optional Description of Group Dakota Keyword Dakota Keyword Description
Optional max_iterations

Number of iterations allowed for optimizers and adaptive UQ methods

Optional convergence_tolerance

Stopping criterion based on objective function or statistics convergence

Optional max_function_evaluations

Number of function evaluations allowed for optimizers

Optional scaling

Turn on scaling for variables, responses, and constraints

Optional model_pointer

Identifier for model block to be used by a method


NLPQL implementation of sequential quadratic programming. The particular SQP implementation in 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.

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.

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.

Expected HDF5 Output

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