IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v18y1970i1p107-118.html
   My bibliography  Save this article

Stability in Nonlinear Programming

Author

Listed:
  • J. P. Evans

    (University of North Carolina, Chapel Hill, North Carolina)

  • F. J. Gould

    (University of North Carolina, Chapel Hill, North Carolina)

Abstract

This paper establishes necessary and sufficient conditions for constraint set stability requiring neither convex constraint functions not convex constraint sets. These conditions then lead to a sufficiency result for the continuity of the optimal objective values as the right-hand side varies. Applications to quasiconvex functions are presented.

Suggested Citation

  • J. P. Evans & F. J. Gould, 1970. "Stability in Nonlinear Programming," Operations Research, INFORMS, vol. 18(1), pages 107-118, February.
    • Handle: RePEc:inm:oropre:v:18:y:1970:i:1:p:107-118
    DOI: 10.1287/opre.18.1.107
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.18.1.107
    Download Restriction: no
    File URL: https://libkey.io/10.1287/opre.18.1.107?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
    ---><---

    Citations

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


    Cited by:

    1. Xiao, Baichun, 1995. "The linear complementarity problem with a parametric input," European Journal of Operational Research, Elsevier, vol. 81(2), pages 420-429, March.
    2. Li, X.B. & Li, S.J., 2014. "Hölder continuity of perturbed solution set for convex optimization problems," Applied Mathematics and Computation, Elsevier, vol. 232(C), pages 908-918.
    3. Frederic H. Murphy, 1973. "Penalty Function Algorithms with the Potential of Limit Convergence," Discussion Papers 30, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    4. E. Muselli, 2000. "Upper and Lower Semicontinuity for Set-Valued Mappings Involving Constraints," Journal of Optimization Theory and Applications, Springer, vol. 106(3), pages 527-550, September.
    5. Giorgio & Cesare, 2018. "A Tutorial on Sensitivity and Stability in Nonlinear Programming and Variational Inequalities under Differentiability Assumptions," DEM Working Papers Series 159, University of Pavia, Department of Economics and Management.
    6. Gregory Cox, 2022. "A Generalized Argmax Theorem with Applications," Papers 2209.08793, arXiv.org.

    More about this item

    Statistics

    Access and download statistics

    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:inm:oropre:v:18:y:1970:i:1:p:107-118. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.