A new exact penalty method for semi-infinite programming problems

In this paper, we consider a class of nonlinear semi-infinite optimization problems. These problems involve continuous inequality constraints that need to be satisfied at every point in an infinite index set, as well as conventional equality and inequality constraints. By introducing a novel penalty...

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Main Authors: Lin, Qun, Loxton, Ryan, Teo, Kok Lay, Wu, Yong Hong, Yu, C.
Format: Journal Article
Published: Elsevier 2014
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/22707
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author Lin, Qun
Loxton, Ryan
Teo, Kok Lay
Wu, Yong Hong
Yu, C.
author_facet Lin, Qun
Loxton, Ryan
Teo, Kok Lay
Wu, Yong Hong
Yu, C.
author_sort Lin, Qun
building Curtin Institutional Repository
collection Online Access
description In this paper, we consider a class of nonlinear semi-infinite optimization problems. These problems involve continuous inequality constraints that need to be satisfied at every point in an infinite index set, as well as conventional equality and inequality constraints. By introducing a novel penalty function to penalize constraint violations, we form an approximate optimization problem in which the penalty function is minimized subject to only bound constraints. We then show that this penalty function is exact—that is, when the penalty parameter is sufficiently large, any local solution of the approximate problem can be used to generate a corresponding local solution of the original problem. On this basis, the original problem can be solved as a sequence of approximate nonlinear programming problems. We conclude the paper with some numerical results demonstrating the applicability of our approach to PID control and filter design.
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publishDate 2014
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spelling curtin-20.500.11937-227072019-02-19T04:26:54Z A new exact penalty method for semi-infinite programming problems Lin, Qun Loxton, Ryan Teo, Kok Lay Wu, Yong Hong Yu, C. Semi-infinite programming Constrained optimization Exact penalty function Nonlinear programming In this paper, we consider a class of nonlinear semi-infinite optimization problems. These problems involve continuous inequality constraints that need to be satisfied at every point in an infinite index set, as well as conventional equality and inequality constraints. By introducing a novel penalty function to penalize constraint violations, we form an approximate optimization problem in which the penalty function is minimized subject to only bound constraints. We then show that this penalty function is exact—that is, when the penalty parameter is sufficiently large, any local solution of the approximate problem can be used to generate a corresponding local solution of the original problem. On this basis, the original problem can be solved as a sequence of approximate nonlinear programming problems. We conclude the paper with some numerical results demonstrating the applicability of our approach to PID control and filter design. 2014 Journal Article http://hdl.handle.net/20.500.11937/22707 10.1016/j.cam.2013.11.010 Elsevier fulltext
spellingShingle Semi-infinite programming
Constrained optimization
Exact penalty function
Nonlinear programming
Lin, Qun
Loxton, Ryan
Teo, Kok Lay
Wu, Yong Hong
Yu, C.
A new exact penalty method for semi-infinite programming problems
title A new exact penalty method for semi-infinite programming problems
title_full A new exact penalty method for semi-infinite programming problems
title_fullStr A new exact penalty method for semi-infinite programming problems
title_full_unstemmed A new exact penalty method for semi-infinite programming problems
title_short A new exact penalty method for semi-infinite programming problems
title_sort new exact penalty method for semi-infinite programming problems
topic Semi-infinite programming
Constrained optimization
Exact penalty function
Nonlinear programming
url http://hdl.handle.net/20.500.11937/22707