WORHP Zen: Parametric Sensitivity Analysis for the Nonlinear Programming Solver WORHP

Renke Kuhlmann (), Sören Geffken () and Christof Büskens ()
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Renke Kuhlmann: University Bremen
Sören Geffken: University Bremen
Christof Büskens: University Bremen

A chapter in Operations Research Proceedings 2017, 2018, pp 649-654 from Springer

Abstract: Abstract Nonlinear optimization problems that arise in real-world applications usually depend on parameter data. Parametric sensitivity analysis is concerned with the effects on the optimal solution caused by changes of these. The calculated sensitivities are of high interest because they improve the understanding of the optimal solution and allow the formulation of real-time capable update algorithms. We present WORHP Zen, a sensitivity analysis module for the nonlinear programming solver WORHP that is capable of the following: (i) Efficient calculation of parametric sensitivities using an existing factorization; (ii) efficient sparse storage of these derivatives, and (iii) real-time updates to calculate an approximated solution of a perturbed optimization problem. An example application of WORHP Zen in the context of parameter identification is presented.

Keywords: Nonlinear programming; Constrained optimization; Sensitivity analysis; Primal-dual method; Large-scale problems (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-319-89920-6_86

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DOI: 10.1007/978-3-319-89920-6_86

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