An inexact proximal method for quasiconvex minimization

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

Research output: Contribution to journalArticlepeer-review

24 Scopus citations


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 languageEnglish
Pages (from-to)721-729
Number of pages9
JournalEuropean Journal of Operational Research
Issue number3
StatePublished - 1 Nov 2015
Externally publishedYes

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.


  • Computing science
  • Global optimization
  • Nonlinear programming
  • Proximal point methods
  • Quasiconvex minimization


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