A new exact penalty function approach to semi-infinite programming problem

In this paper, we propose a new exact penalty function method for solving a class of semi-infinite programming problems (SIPs). We introduce a logarithmic form function of the constraint violation, where the constraint violation is a measure of the violation of the constraints of the current iterate...

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Main Authors: Yu, Changjun, Teo, Kok Lay, Zhang, L.
Other Authors: Themistocles M. Rassias
Format: Book Chapter
Published: Springer 2014
Online Access:http://hdl.handle.net/20.500.11937/16689
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author Yu, Changjun
Teo, Kok Lay
Zhang, L.
author2 Themistocles M. Rassias
author_facet Themistocles M. Rassias
Yu, Changjun
Teo, Kok Lay
Zhang, L.
author_sort Yu, Changjun
building Curtin Institutional Repository
collection Online Access
description In this paper, we propose a new exact penalty function method for solving a class of semi-infinite programming problems (SIPs). We introduce a logarithmic form function of the constraint violation, where the constraint violation is a measure of the violation of the constraints of the current iterate. By appending it to the objective function, we obtain a sequence of approximate conventional unconstrained optimization problem. It is proved that when the penalty parameter is sufficiently large, any local minimizer of the approximate problem is a local minimizer of the original problem. Numerical results show that the proposed method is effective.
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institution Curtin University Malaysia
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last_indexed 2025-11-14T07:17:55Z
publishDate 2014
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spelling curtin-20.500.11937-166892023-02-13T08:01:37Z A new exact penalty function approach to semi-infinite programming problem Yu, Changjun Teo, Kok Lay Zhang, L. Themistocles M. Rassias Christodoulos A. Floudas Sergiy Butenko In this paper, we propose a new exact penalty function method for solving a class of semi-infinite programming problems (SIPs). We introduce a logarithmic form function of the constraint violation, where the constraint violation is a measure of the violation of the constraints of the current iterate. By appending it to the objective function, we obtain a sequence of approximate conventional unconstrained optimization problem. It is proved that when the penalty parameter is sufficiently large, any local minimizer of the approximate problem is a local minimizer of the original problem. Numerical results show that the proposed method is effective. 2014 Book Chapter http://hdl.handle.net/20.500.11937/16689 10.1007/978-1-4939-0808-0_28 Springer restricted
spellingShingle Yu, Changjun
Teo, Kok Lay
Zhang, L.
A new exact penalty function approach to semi-infinite programming problem
title A new exact penalty function approach to semi-infinite programming problem
title_full A new exact penalty function approach to semi-infinite programming problem
title_fullStr A new exact penalty function approach to semi-infinite programming problem
title_full_unstemmed A new exact penalty function approach to semi-infinite programming problem
title_short A new exact penalty function approach to semi-infinite programming problem
title_sort new exact penalty function approach to semi-infinite programming problem
url http://hdl.handle.net/20.500.11937/16689