IDEAS home Printed from https://ideas.repec.org/a/spr/joptap/v167y2015i3d10.1007_s10957-013-0395-4.html
   My bibliography  Save this article

Duality for Closed Convex Functions and Evenly Convex Functions

Author

Listed:
  • M. Volle

    (Avignon University)

  • J. E. Martínez-Legaz

    (Universitat Autònoma de Barcelona)

  • J. Vicente-Pérez

    (University of New South Wales)

Abstract

We introduce two Moreau conjugacies for extended real-valued functions h on a separated locally convex space. In the first scheme, the biconjugate of h coincides with its closed convex hull, whereas, for the second scheme, the biconjugate of h is the evenly convex hull of h. In both cases, the biconjugate coincides with the supremum of the minorants of h that are either continuous affine or closed (respectively, open) halfspaces valley functions.

Suggested Citation

  • M. Volle & J. E. Martínez-Legaz & J. Vicente-Pérez, 2015. "Duality for Closed Convex Functions and Evenly Convex Functions," Journal of Optimization Theory and Applications, Springer, vol. 167(3), pages 985-997, December.
  • Handle: RePEc:spr:joptap:v:167:y:2015:i:3:d:10.1007_s10957-013-0395-4
    DOI: 10.1007/s10957-013-0395-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10957-013-0395-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10957-013-0395-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Goberna, Miguel A. & Rodri'guez, Margarita M.L., 2006. "Analyzing linear systems containing strict inequalities via evenly convex hulls," European Journal of Operational Research, Elsevier, vol. 169(3), pages 1079-1095, March.
    2. Jean-Paul Penot & Michel Volle, 1990. "On Quasi-Convex Duality," Mathematics of Operations Research, INFORMS, vol. 15(4), pages 597-625, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Satoshi Suzuki & Daishi Kuroiwa, 2011. "On Set Containment Characterization and Constraint Qualification for Quasiconvex Programming," Journal of Optimization Theory and Applications, Springer, vol. 149(3), pages 554-563, June.
    2. Satoshi Suzuki, 2010. "Set containment characterization with strict and weak quasiconvex inequalities," Journal of Global Optimization, Springer, vol. 47(2), pages 273-285, June.
    3. Wang, Wei & Xu, Huifu & Ma, Tiejun, 2023. "Optimal scenario-dependent multivariate shortfall risk measure and its application in risk capital allocation," European Journal of Operational Research, Elsevier, vol. 306(1), pages 322-347.
    4. M. Fajardo & J. Vicente-Pérez & M. Rodríguez, 2012. "Infimal convolution, c-subdifferentiability, and Fenchel duality in evenly convex optimization," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(2), pages 375-396, July.
    5. Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci & Luigi Montrucchio, 2011. "Complete Monotone Quasiconcave Duality," Mathematics of Operations Research, INFORMS, vol. 36(2), pages 321-339, May.
    6. Jean-Paul Penot, 2010. "Are dualities appropriate for duality theories in optimization?," Journal of Global Optimization, Springer, vol. 47(3), pages 503-525, July.
    7. Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci, 2015. "On the equality of Clarke-Rockafellar and Greenberg-Pierskalla differentials for monotone and quasiconcave functionals," Working Papers 561, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    8. Margarita M. L. Rodríguez & José Vicente-Pérez, 2017. "On Finite Linear Systems Containing Strict Inequalities," Journal of Optimization Theory and Applications, Springer, vol. 173(1), pages 131-154, April.
    9. Nader Kanzi & Majid Soleimani-damaneh, 2020. "Characterization of the weakly efficient solutions in nonsmooth quasiconvex multiobjective optimization," Journal of Global Optimization, Springer, vol. 77(3), pages 627-641, July.
    10. Maria Arduca & Cosimo Munari, 2021. "Risk measures beyond frictionless markets," Papers 2111.08294, arXiv.org.
    11. Samuel Drapeau & Michael Kupper, 2013. "Risk Preferences and Their Robust Representation," Mathematics of Operations Research, INFORMS, vol. 38(1), pages 28-62, February.
    12. Satoshi Suzuki & Daishi Kuroiwa, 2009. "Set containment characterization for quasiconvex programming," Computational Optimization and Applications, Springer, vol. 45(4), pages 551-563, December.
    13. Elisa Fusco & Bernardo Maggi, 2022. "Computing nonperforming loan prices in banking efficiency analysis," Computational Management Science, Springer, vol. 19(1), pages 1-23, January.
    14. Jean-Paul Penot, 2015. "Projective dualities for quasiconvex problems," Journal of Global Optimization, Springer, vol. 62(3), pages 411-430, July.
    15. S. Mirzadeh & H. Mohebi, 2016. "Abstract Concavity of Increasing Co-radiant and Quasi-Concave Functions with Applications in Mathematical Economics," Journal of Optimization Theory and Applications, Springer, vol. 169(2), pages 443-472, May.
    16. María D. Fajardo & Margarita M. L. Rodríguez & José Vidal, 2016. "Lagrange Duality for Evenly Convex Optimization Problems," Journal of Optimization Theory and Applications, Springer, vol. 168(1), pages 109-128, January.
    17. Cerreia-Vioglio, S. & Maccheroni, F. & Marinacci, M. & Montrucchio, L., 2011. "Uncertainty averse preferences," Journal of Economic Theory, Elsevier, vol. 146(4), pages 1275-1330, July.
    18. Elisa Mastrogiacomo & Emanuela Rosazza Gianin, 2015. "Portfolio Optimization with Quasiconvex Risk Measures," Mathematics of Operations Research, INFORMS, vol. 40(4), pages 1042-1059, October.
    19. Satoshi Suzuki, 2021. "Karush–Kuhn–Tucker type optimality condition for quasiconvex programming in terms of Greenberg–Pierskalla subdifferential," Journal of Global Optimization, Springer, vol. 79(1), pages 191-202, January.
    20. J.P. Penot, 2003. "Lagrangian Approach to Quasiconvex Programing," Journal of Optimization Theory and Applications, Springer, vol. 117(3), pages 637-647, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:joptap:v:167:y:2015:i:3:d:10.1007_s10957-013-0395-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.