A lagrange penalty reformulation method for constrained optimization

A. M. Rubinov; Xiaoqi Yang; Y. Y. Zhou

doi:10.1007/s11590-006-0010-9

A lagrange penalty reformulation method for constrained optimization

A. M. Rubinov, Xiaoqi Yang, Y. Y. Zhou

Research output: Journal article publication › Journal article › Academic research › peer-review

3 Citations (Scopus)

Abstract

In this paper a constrained optimization problem is transformed into an equivalent one in terms of an auxiliary penalty function. A Lagrange function method is then applied to this transformed problem. Zero duality gap and exact penalty results are obtained without any coercivity assumption on either the objective function or constraint functions.

Original language	English
Pages (from-to)	145-154
Number of pages	10
Journal	Optimization Letters
Volume	1
Issue number	2
DOIs	https://doi.org/10.1007/s11590-006-0010-9
Publication status	Published - 1 Mar 2007

Keywords

Augmented penalty function
Constrained optimization
Non-coercivity
Zero duality gap

ASJC Scopus subject areas

Control and Optimization

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10.1007/s11590-006-0010-9

Cite this

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title = "A lagrange penalty reformulation method for constrained optimization",

abstract = "In this paper a constrained optimization problem is transformed into an equivalent one in terms of an auxiliary penalty function. A Lagrange function method is then applied to this transformed problem. Zero duality gap and exact penalty results are obtained without any coercivity assumption on either the objective function or constraint functions.",

keywords = "Augmented penalty function, Constrained optimization, Non-coercivity, Zero duality gap",

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AU - Yang, Xiaoqi

AU - Zhou, Y. Y.

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N2 - In this paper a constrained optimization problem is transformed into an equivalent one in terms of an auxiliary penalty function. A Lagrange function method is then applied to this transformed problem. Zero duality gap and exact penalty results are obtained without any coercivity assumption on either the objective function or constraint functions.

AB - In this paper a constrained optimization problem is transformed into an equivalent one in terms of an auxiliary penalty function. A Lagrange function method is then applied to this transformed problem. Zero duality gap and exact penalty results are obtained without any coercivity assumption on either the objective function or constraint functions.

KW - Augmented penalty function

KW - Constrained optimization

KW - Non-coercivity

KW - Zero duality gap

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DO - 10.1007/s11590-006-0010-9

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JO - Optimization Letters

JF - Optimization Letters

IS - 2

ER -

A lagrange penalty reformulation method for constrained optimization

Abstract

Keywords

ASJC Scopus subject areas

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