.. _method-nlpql_sqp: """"""""" nlpql_sqp """"""""" NLPQL Sequential Quadratic Program **Topics** package_nlpql, sequential_quadratic_programming, local_optimization_methods .. toctree:: :hidden: :maxdepth: 1 method-nlpql_sqp-max_iterations method-nlpql_sqp-convergence_tolerance method-nlpql_sqp-max_function_evaluations method-nlpql_sqp-scaling method-nlpql_sqp-model_pointer **Specification** - *Alias:* None - *Arguments:* None **Child Keywords:** +-------------------------+--------------------+------------------------------+---------------------------------------------+ | Required/Optional | Description of | Dakota Keyword | Dakota Keyword Description | | | Group | | | +=========================+====================+==============================+=============================================+ | 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 | +----------------------------------------------+------------------------------+---------------------------------------------+ .. __: method-nlpql_sqp-max_iterations.html __ method-nlpql_sqp-convergence_tolerance.html __ method-nlpql_sqp-max_function_evaluations.html __ method-nlpql_sqp-scaling.html __ method-nlpql_sqp-model_pointer.html **Description** 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 :dakkw:`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 :dakkw:`responses-objective_functions`) are specified) - :ref:`hdf5_results-best_constraints` - :ref:`hdf5_results-calibration` (when :dakkw:`responses-calibration_terms` are specified)