A power penalty approach to a discretized obstacle problem with nonlinear constraints

A novel power penalty method is proposed to solve a nonlinear obstacle problem with nonlinear constraints arising from the discretization of an infinite-dimensional optimization problem. This approach is based on the formulation of a penalty equation approximating the mixed nonlinear complementarity...

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Main Authors: Zhao, J., Wang, Song
Format: Journal Article
Published: Springer Verlag 2019
Online Access:http://hdl.handle.net/20.500.11937/71030
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author Zhao, J.
Wang, Song
author_facet Zhao, J.
Wang, Song
author_sort Zhao, J.
building Curtin Institutional Repository
collection Online Access
description A novel power penalty method is proposed to solve a nonlinear obstacle problem with nonlinear constraints arising from the discretization of an infinite-dimensional optimization problem. This approach is based on the formulation of a penalty equation approximating the mixed nonlinear complementarity problem arising from the Karush–Kuhn–Tucker conditions of the optimization problem. We show that the solution to the penalty equation converges to that of the complementarity problem with an exponential convergence rate depending on the parameters used in the penalty equation. Numerical experiments are performed to confirm the theoretical convergence rate established.
first_indexed 2025-11-14T10:46:30Z
format Journal Article
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T10:46:30Z
publishDate 2019
publisher Springer Verlag
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-710302019-10-14T04:13:33Z A power penalty approach to a discretized obstacle problem with nonlinear constraints Zhao, J. Wang, Song A novel power penalty method is proposed to solve a nonlinear obstacle problem with nonlinear constraints arising from the discretization of an infinite-dimensional optimization problem. This approach is based on the formulation of a penalty equation approximating the mixed nonlinear complementarity problem arising from the Karush–Kuhn–Tucker conditions of the optimization problem. We show that the solution to the penalty equation converges to that of the complementarity problem with an exponential convergence rate depending on the parameters used in the penalty equation. Numerical experiments are performed to confirm the theoretical convergence rate established. 2019 Journal Article http://hdl.handle.net/20.500.11937/71030 10.1007/s11590-018-1354-7 Springer Verlag restricted
spellingShingle Zhao, J.
Wang, Song
A power penalty approach to a discretized obstacle problem with nonlinear constraints
title A power penalty approach to a discretized obstacle problem with nonlinear constraints
title_full A power penalty approach to a discretized obstacle problem with nonlinear constraints
title_fullStr A power penalty approach to a discretized obstacle problem with nonlinear constraints
title_full_unstemmed A power penalty approach to a discretized obstacle problem with nonlinear constraints
title_short A power penalty approach to a discretized obstacle problem with nonlinear constraints
title_sort power penalty approach to a discretized obstacle problem with nonlinear constraints
url http://hdl.handle.net/20.500.11937/71030