IDEAS home Printed from https://ideas.repec.org/a/spr/joptap/v106y2000i2d10.1023_a1004695229456.html
   My bibliography  Save this article

Approximate Efficiency and Scalar Stationarity in Unbounded Nonsmooth Convex Vector Optimization Problems

Author

Listed:
  • S. BOLINTINÉANU

    (Université de Perpignan)

Abstract

We deal with extended-valued nonsmooth convex vector optimization problems in infinite-dimensional spaces where the solution set (the weakly efficient set) may be empty. We characterize the class of convex vector functions having the property that every scalarly stationary sequence is a weakly-efficient sequence. We generalize the results obained in the scalar case by Auslender and Crouzeix about asymptotically well-behaved convex functions and improve substantially the few results known in the vector case.

Suggested Citation

  • S. Bolintinéanu, 2000. "Approximate Efficiency and Scalar Stationarity in Unbounded Nonsmooth Convex Vector Optimization Problems," Journal of Optimization Theory and Applications, Springer, vol. 106(2), pages 265-296, August.
  • Handle: RePEc:spr:joptap:v:106:y:2000:i:2:d:10.1023_a:1004695229456
    DOI: 10.1023/A:1004695229456
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1023/A:1004695229456
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1023/A:1004695229456?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ceng, Lu-Chuan & Yao, Jen-Chih, 2007. "Approximate proximal methods in vector optimization," European Journal of Operational Research, Elsevier, vol. 183(1), pages 1-19, November.
    2. L. C. Ceng & B. S. Mordukhovich & J. C. Yao, 2010. "Hybrid Approximate Proximal Method with Auxiliary Variational Inequality for Vector Optimization," Journal of Optimization Theory and Applications, Springer, vol. 146(2), pages 267-303, August.

    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:106:y:2000:i:2:d:10.1023_a:1004695229456. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.