A class of convexification and concavification methods for non-monotone optimization problems

Z. Y. Wu; Heung Wing Joseph Lee; X. M. Yang

doi:10.1080/02331930500342807

A class of convexification and concavification methods for non-monotone optimization problems

Z. Y. Wu
, Heung Wing Joseph Lee
, X. M. Yang

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

3 Citations (Scopus)

Abstract

A class of convexification and concavification methods are proposed for solving some classes of non-monotone optimization problems. It is shown that some classes of non-monotone optimization problems can be converted into better structured optimization problems, such as, concave minimization problems, reverse convex programming problems, and canonical D.C. programming problems by the proposed convexification and concavification methods. The equivalence between the original problem and the converted better structured optimization problem is established.

Original language	English
Pages (from-to)	605-625
Number of pages	21
Journal	Optimization
Volume	54
Issue number	6
DOIs	https://doi.org/10.1080/02331930500342807
Publication status	Published - 1 Dec 2005

Keywords

Concavification
Convexification
Global optimization

ASJC Scopus subject areas

Applied Mathematics
Control and Optimization
Management Science and Operations Research

More information

10.1080/02331930500342807

Cite this

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abstract = "A class of convexification and concavification methods are proposed for solving some classes of non-monotone optimization problems. It is shown that some classes of non-monotone optimization problems can be converted into better structured optimization problems, such as, concave minimization problems, reverse convex programming problems, and canonical D.C. programming problems by the proposed convexification and concavification methods. The equivalence between the original problem and the converted better structured optimization problem is established.",

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AB - A class of convexification and concavification methods are proposed for solving some classes of non-monotone optimization problems. It is shown that some classes of non-monotone optimization problems can be converted into better structured optimization problems, such as, concave minimization problems, reverse convex programming problems, and canonical D.C. programming problems by the proposed convexification and concavification methods. The equivalence between the original problem and the converted better structured optimization problem is established.

KW - Concavification

KW - Convexification

KW - Global optimization

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A class of convexification and concavification methods for non-monotone optimization problems

Abstract

Keywords

ASJC Scopus subject areas

More information

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