IDEAS home Printed from https://ideas.repec.org/a/spr/joptap/v192y2022i1d10.1007_s10957-021-01952-6.html
   My bibliography  Save this article

Subdifferentials of the Marginal Functions in Parametric Convex Optimization via Intersection Formulas

Author

Listed:
  • Duong Thi Viet An

    (Hangzhou Dianzi University
    Thai Nguyen University of Sciences)

  • Abderrahim Jourani

    (Université de Bourgogne Franche-Comté)

Abstract

The aim of the present work is to use a metric intersection formula to estimate the subdifferential of the marginal function in the convex setting. This intersection formula includes many interesting situations in parametric convex programming, including the polyhedral one. It is expressed in terms of the objective function and the constrained multivalued mapping which govern the parametric program.

Suggested Citation

  • Duong Thi Viet An & Abderrahim Jourani, 2022. "Subdifferentials of the Marginal Functions in Parametric Convex Optimization via Intersection Formulas," Journal of Optimization Theory and Applications, Springer, vol. 192(1), pages 82-96, January.
  • Handle: RePEc:spr:joptap:v:192:y:2022:i:1:d:10.1007_s10957-021-01952-6
    DOI: 10.1007/s10957-021-01952-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10957-021-01952-6
    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/s10957-021-01952-6?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. Duong Thi Viet An & Jen-Chih Yao, 2016. "Further Results on Differential Stability of Convex Optimization Problems," Journal of Optimization Theory and Applications, Springer, vol. 170(1), pages 28-42, July.
    2. Bernhard Gollan, 1984. "On The Marginal Function in Nonlinear Programming," Mathematics of Operations Research, INFORMS, vol. 9(2), pages 208-221, May.
    3. Frank H. Clarke, 1976. "A New Approach to Lagrange Multipliers," Mathematics of Operations Research, INFORMS, vol. 1(2), pages 165-174, May.
    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. Casey Rothschild & Florian Scheuer, 2014. "A Theory of Income Taxation under Multidimensional Skill Heterogeneity," NBER Working Papers 19822, National Bureau of Economic Research, Inc.
    2. Enrico Bellino, 2010. "Comment To ‘Commodity Content . . .’ By Fujimoto And Opocher," Metroeconomica, Wiley Blackwell, vol. 61(4), pages 749-753, November.
    3. D.P. Bertsekas & A.E. Ozdaglar, 2002. "Pseudonormality and a Lagrange Multiplier Theory for Constrained Optimization," Journal of Optimization Theory and Applications, Springer, vol. 114(2), pages 287-343, August.
    4. Nguyen Thi Hang & Jen-Chih Yao, 2016. "Sufficient conditions for error bounds of difference functions and applications," Journal of Global Optimization, Springer, vol. 66(3), pages 439-456, November.
    5. J. Zhai & X. X. Huang, 2014. "Calmness and Exact Penalization in Vector Optimization under Nonlinear Perturbations," Journal of Optimization Theory and Applications, Springer, vol. 162(3), pages 856-872, September.
    6. Kuang Bai & Yixia Song & Jin Zhang, 2023. "Second-Order Enhanced Optimality Conditions and Constraint Qualifications," Journal of Optimization Theory and Applications, Springer, vol. 198(3), pages 1264-1284, September.
    7. Y. Y. Zhou & X. Q. Yang, 2009. "Duality and Penalization in Optimization via an Augmented Lagrangian Function with Applications," Journal of Optimization Theory and Applications, Springer, vol. 140(1), pages 171-188, January.
    8. Florian Scheuer & Alexander Wolitzky, 2016. "Capital Taxation under Political Constraints," American Economic Review, American Economic Association, vol. 106(8), pages 2304-2328, August.
    9. A. Uderzo, 2014. "On Lipschitz Semicontinuity Properties of Variational Systems with Application to Parametric Optimization," Journal of Optimization Theory and Applications, Springer, vol. 162(1), pages 47-78, July.
    10. Casey Rothschild & Florian Scheuer, 2016. "Optimal Taxation with Rent-Seeking," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 83(3), pages 1225-1262.
    11. Duong Thi Viet An & Jen-Chih Yao, 2019. "Differential Stability of Convex Optimization Problems with Possibly Empty Solution Sets," Journal of Optimization Theory and Applications, Springer, vol. 181(1), pages 126-143, April.
    12. Yuntong Wang, 2014. "Envelope Theorem without Differentiability," Working Papers 1404, University of Windsor, Department of Economics.
    13. M. A. Goberna & M. A. López, 2018. "Recent contributions to linear semi-infinite optimization: an update," Annals of Operations Research, Springer, vol. 271(1), pages 237-278, December.
    14. Zachary Bethune & Tai-Wei Hu & Guillaume Rocheteau, 2018. "Optimal Credit Cycles," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 27, pages 231-245, January.
    15. Alexander J. Zaslavski, 2007. "Existence of Approximate Exact Penalty in Constrained Optimization," Mathematics of Operations Research, INFORMS, vol. 32(2), pages 484-495, May.
    16. Le Phuoc Hai & Phan Quoc Khanh & Antoine Soubeyran, 2022. "General Versions of the Ekeland Variational Principle: Ekeland Points and Stop and Go Dynamics," Journal of Optimization Theory and Applications, Springer, vol. 195(1), pages 347-373, October.
    17. Duong Thi Viet An & Jen-Chih Yao, 2016. "Further Results on Differential Stability of Convex Optimization Problems," Journal of Optimization Theory and Applications, Springer, vol. 170(1), pages 28-42, July.
    18. Giorgio Giorgi, 2021. "Some Classical Directional Derivatives and Their Use in Optimization," DEM Working Papers Series 204, University of Pavia, Department of Economics and Management.
    19. Vadim Bondarevsky & Alexey Leschov & Leonid Minchenko, 2016. "Value Functions and Their Directional Derivatives in Parametric Nonlinear Programming," Journal of Optimization Theory and Applications, Springer, vol. 171(2), pages 440-464, November.
    20. Giorgio Giorgi, 2017. "Minimum Principle-Type Necessary Optimality Conditions in Scalar and Vector Optimization. An Account," Journal of Mathematics Research, Canadian Center of Science and Education, vol. 9(4), pages 168-184, 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:192:y:2022:i:1:d:10.1007_s10957-021-01952-6. 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.