IDEAS home Printed from https://ideas.repec.org/a/spr/dyngam/v15y2025i1d10.1007_s13235-024-00566-7.html
   My bibliography  Save this article

Pareto Optimal Cooperative Control of Mean-Field Backward Stochastic Differential System in Finite Horizon

Author

Listed:
  • G. Saranya

    (The Gandhigram Rural Institute (Deemed to be University))

  • R. Deepa

    (Panimalar Engineering College)

  • P. Muthukumar

    (The Gandhigram Rural Institute (Deemed to be University))

Abstract

This research article aims to investigate a new type of Pareto cooperative differential game governed by backward stochastic differential equations of mean-field type. By the characterization of Pareto optimal solutions, the proposed Pareto game problem is converted into a set of optimal control problems with single weighted objective function which is constrained by mean-field backward stochastic differential equations. First, we derive the necessary conditions for Pareto optimality of the proposed system in finite time horizon. Next, the sufficient conditions are established with the conclusion that the necessary conditions are sufficient under some convexity assumptions. Finally, for the better understanding of theoretical results, we discuss the linear quadratic optimal control problem and a mathematical transportation problem.

Suggested Citation

  • G. Saranya & R. Deepa & P. Muthukumar, 2025. "Pareto Optimal Cooperative Control of Mean-Field Backward Stochastic Differential System in Finite Horizon," Dynamic Games and Applications, Springer, vol. 15(1), pages 279-305, March.
    • Handle: RePEc:spr:dyngam:v:15:y:2025:i:1:d:10.1007_s13235-024-00566-7
    DOI: 10.1007/s13235-024-00566-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13235-024-00566-7
    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/s13235-024-00566-7?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.

    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:dyngam:v:15:y:2025:i:1:d:10.1007_s13235-024-00566-7. 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.