IDEAS home Printed from https://ideas.repec.org/a/spr/joptap/v162y2014i3d10.1007_s10957-013-0338-0.html
   My bibliography  Save this article

Calmness and Exact Penalization in Vector Optimization under Nonlinear Perturbations

Author

Listed:
  • J. Zhai

    (Chongqing University)

  • X. X. Huang

    (Chongqing University)

Abstract

In this paper, we study the relationship between calmness and exact penalization for vector optimization problems under nonlinear perturbations. Some sufficient conditions for the problem calmness are also derived.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:joptap:v:162:y:2014:i:3:d:10.1007_s10957-013-0338-0
    DOI: 10.1007/s10957-013-0338-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10957-013-0338-0
    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/s10957-013-0338-0?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. Frank H. Clarke, 1976. "A New Approach to Lagrange Multipliers," Mathematics of Operations Research, INFORMS, vol. 1(2), pages 165-174, May.
    2. X. X. Huang & X. Q. Yang, 2003. "A Unified Augmented Lagrangian Approach to Duality and Exact Penalization," Mathematics of Operations Research, INFORMS, vol. 28(3), pages 533-552, August.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Xin Shen & John E. Mitchell, 2018. "A penalty method for rank minimization problems in symmetric matrices," Computational Optimization and Applications, Springer, vol. 71(2), pages 353-380, November.

    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. 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.
    2. Enrico Bellino, 2010. "Comment To ‘Commodity Content . . .’ By Fujimoto And Opocher," Metroeconomica, Wiley Blackwell, vol. 61(4), pages 749-753, November.
    3. Yaohua Hu & Carisa Kwok Wai Yu & Xiaoqi Yang, 2019. "Incremental quasi-subgradient methods for minimizing the sum of quasi-convex functions," Journal of Global Optimization, Springer, vol. 75(4), pages 1003-1028, December.
    4. 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.
    5. Kaiwen Meng & Xiaoqi Yang, 2015. "First- and Second-Order Necessary Conditions Via Exact Penalty Functions," Journal of Optimization Theory and Applications, Springer, vol. 165(3), pages 720-752, June.
    6. Florian Scheuer & Alexander Wolitzky, 2016. "Capital Taxation under Political Constraints," American Economic Review, American Economic Association, vol. 106(8), pages 2304-2328, August.
    7. S. K. Zhu & S. J. Li, 2014. "Unified Duality Theory for Constrained Extremum Problems. Part II: Special Duality Schemes," Journal of Optimization Theory and Applications, Springer, vol. 161(3), pages 763-782, June.
    8. 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.
    9. M. V. Dolgopolik, 2018. "A Unified Approach to the Global Exactness of Penalty and Augmented Lagrangian Functions I: Parametric Exactness," Journal of Optimization Theory and Applications, Springer, vol. 176(3), pages 728-744, March.
    10. Qian Liu & Wan Tang & Xin Yang, 2009. "Properties of saddle points for generalized augmented Lagrangian," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 69(1), pages 111-124, March.
    11. Yuntong Wang, 2014. "Envelope Theorem without Differentiability," Working Papers 1404, University of Windsor, Department of Economics.
    12. Boshi Tian & Yaohua Hu & Xiaoqi Yang, 2015. "A box-constrained differentiable penalty method for nonlinear complementarity problems," Journal of Global Optimization, Springer, vol. 62(4), pages 729-747, August.
    13. Angelia Nedić & Asuman Ozdaglar, 2008. "Separation of Nonconvex Sets with General Augmenting Functions," Mathematics of Operations Research, INFORMS, vol. 33(3), pages 587-605, August.
    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. Yaohua Hu & Chong Li & Kaiwen Meng & Xiaoqi Yang, 2021. "Linear convergence of inexact descent method and inexact proximal gradient algorithms for lower-order regularization problems," Journal of Global Optimization, Springer, vol. 79(4), pages 853-883, April.
    16. Ma, Jun & Nault, Barrie R. & Tu, Yiliu (Paul), 2023. "Customer segmentation, pricing, and lead time decisions: A stochastic-user-equilibrium perspective," International Journal of Production Economics, Elsevier, vol. 264(C).
    17. R. S. Burachik & X. Q. Yang & Y. Y. Zhou, 2017. "Existence of Augmented Lagrange Multipliers for Semi-infinite Programming Problems," Journal of Optimization Theory and Applications, Springer, vol. 173(2), pages 471-503, May.
    18. Hu, Yaohua & Li, Gongnong & Yu, Carisa Kwok Wai & Yip, Tsz Leung, 2022. "Quasi-convex feasibility problems: Subgradient methods and convergence rates," European Journal of Operational Research, Elsevier, vol. 298(1), pages 45-58.
    19. Xiaoqi Yang & Chenchen Zu, 2022. "Convergence of Inexact Quasisubgradient Methods with Extrapolation," Journal of Optimization Theory and Applications, Springer, vol. 193(1), pages 676-703, June.
    20. C. Lalitha, 2010. "A new augmented Lagrangian approach to duality and exact penalization," Journal of Global Optimization, Springer, vol. 46(2), pages 233-245, February.

    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:162:y:2014:i:3:d:10.1007_s10957-013-0338-0. 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.