IDEAS home Printed from https://ideas.repec.org/a/spr/joptap/v144y2010i3d10.1007_s10957-009-9615-3.html
   My bibliography  Save this article

Inexact A-Proximal Point Algorithm and Applications to Nonlinear Variational Inclusion Problems

Author

Listed:
  • R. P. Agarwal

    (Florida Institute of Technology)

  • R. U. Verma

    (International Publications (USA))

Abstract

A generalization to the Rockafellar theorem (1976) on the linear convergence in the context of approximating a solution to a general class of inclusion problems involving set-valued A-maximal relaxed monotone mappings using the proximal point algorithm in a real Hilbert space setting is given. There exists a vast literature on this theorem, but most of the investigations are focused on relaxing the proximal point algorithm and applying it to the inclusion problems. The general framework for A-maximal relaxed monotonicity generalizes the theory of set-valued maximal monotone mappings, including H-maximal monotone mappings. The obtained results are general in nature, while application-oriented as well.

Suggested Citation

  • R. P. Agarwal & R. U. Verma, 2010. "Inexact A-Proximal Point Algorithm and Applications to Nonlinear Variational Inclusion Problems," Journal of Optimization Theory and Applications, Springer, vol. 144(3), pages 431-444, March.
  • Handle: RePEc:spr:joptap:v:144:y:2010:i:3:d:10.1007_s10957-009-9615-3
    DOI: 10.1007/s10957-009-9615-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10957-009-9615-3
    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/s10957-009-9615-3?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. R. T. Rockafellar, 1976. "Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming," Mathematics of Operations Research, INFORMS, vol. 1(2), pages 97-116, May.
    2. R. U. Verma, 2004. "Generalized System for Relaxed Cocoercive Variational Inequalities and Projection Methods," Journal of Optimization Theory and Applications, Springer, vol. 121(1), pages 203-210, April.
    3. R. U. Verma, 2006. "A-Monotonicity and Its Role in Nonlinear Variational Inclusions," Journal of Optimization Theory and Applications, Springer, vol. 129(3), pages 457-467, June.
    4. R. U. Verma, 2006. "General System of A-Monotone Nonlinear Variational Inclusion Problems with Applications," Journal of Optimization Theory and Applications, Springer, vol. 131(1), pages 151-157, October.
    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. R. P. Agarwal & R. U. Verma, 2009. "Role of Relative A-Maximal Monotonicity in Overrelaxed Proximal-Point Algorithms with Applications," Journal of Optimization Theory and Applications, Springer, vol. 143(1), pages 1-15, October.
    2. Ram U. Verma, 2012. "General Class of Implicit Variational Inclusions and Graph Convergence on A-Maximal Relaxed Monotonicity," Journal of Optimization Theory and Applications, Springer, vol. 155(1), pages 196-214, October.
    3. Jean-Pierre Crouzeix & Abdelhak Hassouni & Eladio OcaƱa, 2023. "A Short Note on the Twice Differentiability of the Marginal Function of a Convex Function," Journal of Optimization Theory and Applications, Springer, vol. 198(2), pages 857-867, August.
    4. Bingsheng He & Li-Zhi Liao & Xiang Wang, 2012. "Proximal-like contraction methods for monotone variational inequalities in a unified framework I: Effective quadruplet and primary methods," Computational Optimization and Applications, Springer, vol. 51(2), pages 649-679, March.
    5. Xiaoming Yuan, 2011. "An improved proximal alternating direction method for monotone variational inequalities with separable structure," Computational Optimization and Applications, Springer, vol. 49(1), pages 17-29, May.
    6. Zhu, Daoli & Marcotte, Patrice, 1995. "Coupling the auxiliary problem principle with descent methods of pseudoconvex programming," European Journal of Operational Research, Elsevier, vol. 83(3), pages 670-685, June.
    7. Guo, Zhaomiao & Fan, Yueyue, 2017. "A Stochastic Multi-Agent Optimization Model for Energy Infrastructure Planning Under Uncertainty and Competition," Institute of Transportation Studies, Working Paper Series qt89s5s8hn, Institute of Transportation Studies, UC Davis.
    8. R. S. Burachik & S. Scheimberg & B. F. Svaiter, 2001. "Robustness of the Hybrid Extragradient Proximal-Point Algorithm," Journal of Optimization Theory and Applications, Springer, vol. 111(1), pages 117-136, October.
    9. A. F. Izmailov & M. V. Solodov, 2022. "Perturbed Augmented Lagrangian Method Framework with Applications to Proximal and Smoothed Variants," Journal of Optimization Theory and Applications, Springer, vol. 193(1), pages 491-522, June.
    10. Kyung Soo Kim, 2018. "System of Extended General Variational Inequalities for Relaxed Cocoercive Mappings in Hilbert Space," Mathematics, MDPI, vol. 6(10), pages 1-12, October.
    11. M. Kyono & M. Fukushima, 2000. "Nonlinear Proximal Decomposition Method for Convex Programming," Journal of Optimization Theory and Applications, Springer, vol. 106(2), pages 357-372, August.
    12. Ya-Feng Liu & Xin Liu & Shiqian Ma, 2019. "On the Nonergodic Convergence Rate of an Inexact Augmented Lagrangian Framework for Composite Convex Programming," Mathematics of Operations Research, INFORMS, vol. 44(2), pages 632-650, May.
    13. J. R. Birge & L. Qi & Z. Wei, 1998. "Convergence Analysis of Some Methods for Minimizing a Nonsmooth Convex Function," Journal of Optimization Theory and Applications, Springer, vol. 97(2), pages 357-383, May.
    14. Bingsheng He & Li-Zhi Liao & Xiang Wang, 2012. "Proximal-like contraction methods for monotone variational inequalities in a unified framework II: general methods and numerical experiments," Computational Optimization and Applications, Springer, vol. 51(2), pages 681-708, March.
    15. Jonathan Eckstein, 2017. "A Simplified Form of Block-Iterative Operator Splitting and an Asynchronous Algorithm Resembling the Multi-Block Alternating Direction Method of Multipliers," Journal of Optimization Theory and Applications, Springer, vol. 173(1), pages 155-182, April.
    16. N. El Farouq & G. Cohen, 1998. "Progressive Regularization of Variational Inequalities and Decomposition Algorithms," Journal of Optimization Theory and Applications, Springer, vol. 97(2), pages 407-433, May.
    17. Bingsheng He & Min Tao & Xiaoming Yuan, 2017. "Convergence Rate Analysis for the Alternating Direction Method of Multipliers with a Substitution Procedure for Separable Convex Programming," Mathematics of Operations Research, INFORMS, vol. 42(3), pages 662-691, August.
    18. A. Kaplan & R. Tichatschke, 1998. "Proximal Methods in View of Interior-Point Strategies," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 399-429, August.
    19. Jonathan Eckstein & Paulo Silva, 2010. "Proximal methods for nonlinear programming: double regularization and inexact subproblems," Computational Optimization and Applications, Springer, vol. 46(2), pages 279-304, June.
    20. Felipe Alvarez & Miguel Carrasco & Karine Pichard, 2005. "Convergence of a Hybrid Projection-Proximal Point Algorithm Coupled with Approximation Methods in Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 30(4), pages 966-984, November.

    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:144:y:2010:i:3:d:10.1007_s10957-009-9615-3. 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.