An inexact proximal method for quasiconvex minimization

E. A. Papa Quiroz; L. Mallma Ramirez; P. R. Oliveira

doi:10.1016/j.ejor.2015.05.041

An inexact proximal method for quasiconvex minimization

E. A. Papa Quiroz, L. Mallma Ramirez, P. R. Oliveira

Research output: Contribution to journal › Article › peer-review

28 Scopus citations

Abstract

In this paper we propose an inexact proximal point method to solve constrained minimization problems with locally Lipschitz quasiconvex objective functions. Assuming that the function is also bounded from below, lower semicontinuous and using proximal distances, we show that the sequence generated for the method converges to a stationary point of the problem.

Original language	English
Pages (from-to)	721-729
Number of pages	9
Journal	European Journal of Operational Research
Volume	246
Issue number	3
DOIs	https://doi.org/10.1016/j.ejor.2015.05.041
State	Published - 1 Nov 2015
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.

Keywords

Computing science
Global optimization
Nonlinear programming
Proximal point methods
Quasiconvex minimization

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10.1016/j.ejor.2015.05.041

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keywords = "Computing science, Global optimization, Nonlinear programming, Proximal point methods, Quasiconvex minimization",

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note = "Publisher Copyright: {\textcopyright} 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.",

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AU - Mallma Ramirez, L.

AU - Oliveira, P. R.

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PY - 2015/11/1

Y1 - 2015/11/1

N2 - In this paper we propose an inexact proximal point method to solve constrained minimization problems with locally Lipschitz quasiconvex objective functions. Assuming that the function is also bounded from below, lower semicontinuous and using proximal distances, we show that the sequence generated for the method converges to a stationary point of the problem.

AB - In this paper we propose an inexact proximal point method to solve constrained minimization problems with locally Lipschitz quasiconvex objective functions. Assuming that the function is also bounded from below, lower semicontinuous and using proximal distances, we show that the sequence generated for the method converges to a stationary point of the problem.

KW - Computing science

KW - Global optimization

KW - Nonlinear programming

KW - Proximal point methods

KW - Quasiconvex minimization

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M3 - Artículo

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EP - 729

JO - European Journal of Operational Research

JF - European Journal of Operational Research

IS - 3

ER -

An inexact proximal method for quasiconvex minimization

Abstract

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Keywords

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