IDEAS home Printed from https://ideas.repec.org/a/spr/jglopt/v72y2018i4d10.1007_s10898-018-0664-8.html
   My bibliography  Save this article

Variational inequality formulation for the games with random payoffs

Author

Listed:
  • Vikas Vikram Singh

    (Indian Institute of Technology Delhi)

  • Abdel Lisser

    (Université Paris Sud)

Abstract

We consider an n-player non-cooperative game with random payoffs and continuous strategy set for each player. The random payoffs of each player are defined using a finite dimensional random vector. We formulate this problem as a chance-constrained game by defining the payoff function of each player using a chance constraint. We first consider the case where the continuous strategy set of each player does not depend on the strategies of other players. If a random vector defining the payoffs of each player follows a multivariate elliptically symmetric distribution, we show that there exists a Nash equilibrium. We characterize the set of Nash equilibria using the solution set of a variational inequality (VI) problem. Next, we consider the case where the continuous strategy set of each player is defined by a shared constraint set. In this case, we show that there exists a generalized Nash equilibrium for elliptically symmetric distributed payoffs. Under certain conditions, we characterize the set of a generalized Nash equilibria using the solution set of a VI problem. As an application, the random payoff games arising from electricity market are studied under chance-constrained game framework.

Suggested Citation

  • Vikas Vikram Singh & Abdel Lisser, 2018. "Variational inequality formulation for the games with random payoffs," Journal of Global Optimization, Springer, vol. 72(4), pages 743-760, December.
  • Handle: RePEc:spr:jglopt:v:72:y:2018:i:4:d:10.1007_s10898-018-0664-8
    DOI: 10.1007/s10898-018-0664-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10898-018-0664-8
    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/s10898-018-0664-8?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. Cheng, Jianqiang & Leung, Janny & Lisser, Abdel, 2016. "Random-payoff two-person zero-sum game with joint chance constraints," European Journal of Operational Research, Elsevier, vol. 252(1), pages 213-219.
    2. Ilan Adler, 2013. "The equivalence of linear programs and zero-sum games," International Journal of Game Theory, Springer;Game Theory Society, vol. 42(1), pages 165-177, February.
    3. B. Jadamba & F. Raciti, 2015. "Variational Inequality Approach to Stochastic Nash Equilibrium Problems with an Application to Cournot Oligopoly," Journal of Optimization Theory and Applications, Springer, vol. 165(3), pages 1050-1070, June.
    4. Huifu Xu & Dali Zhang, 2013. "Stochastic Nash equilibrium problems: sample average approximation and applications," Computational Optimization and Applications, Springer, vol. 55(3), pages 597-645, July.
    5. Roger A. Blau, 1974. "Random-Payoff Two-Person Zero-Sum Games," Operations Research, INFORMS, vol. 22(6), pages 1243-1251, December.
    6. A. Charnes & W. W. Cooper, 1963. "Deterministic Equivalents for Optimizing and Satisficing under Chance Constraints," Operations Research, INFORMS, vol. 11(1), pages 18-39, February.
    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. Rossana Riccardi & Giorgia Oggioni & Elisabetta Allevi & Abdel Lisser, 2023. "Complementarity formulation of games with random payoffs," Computational Management Science, Springer, vol. 20(1), pages 1-32, December.

    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. Vikas Vikram Singh & Abdel Lisser, 2018. "A Characterization of Nash Equilibrium for the Games with Random Payoffs," Journal of Optimization Theory and Applications, Springer, vol. 178(3), pages 998-1013, September.
    2. Singh, Vikas Vikram & Lisser, Abdel & Arora, Monika, 2021. "An equivalent mathematical program for games with random constraints," Statistics & Probability Letters, Elsevier, vol. 174(C).
    3. Singh, Vikas Vikram & Lisser, Abdel, 2019. "A second-order cone programming formulation for two player zero-sum games with chance constraints," European Journal of Operational Research, Elsevier, vol. 275(3), pages 839-845.
    4. Shen Peng & Navnit Yadav & Abdel Lisser & Vikas Vikram Singh, 2021. "Chance-constrained games with mixture distributions," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 94(1), pages 71-97, August.
    5. Chen, Shun & Zhao, Xudong & Chen, Zhilong & Hou, Benwei & Wu, Yipeng, 2022. "A game-theoretic method to optimize allocation of defensive resource to protect urban water treatment plants against physical attacks," International Journal of Critical Infrastructure Protection, Elsevier, vol. 36(C).
    6. Minjiao Zhang & Simge Küçükyavuz & Saumya Goel, 2014. "A Branch-and-Cut Method for Dynamic Decision Making Under Joint Chance Constraints," Management Science, INFORMS, vol. 60(5), pages 1317-1333, May.
    7. Hang Li & Zhe Zhang & Xianggen Yin & Buhan Zhang, 2020. "Preventive Security-Constrained Optimal Power Flow with Probabilistic Guarantees," Energies, MDPI, vol. 13(9), pages 1-13, May.
    8. Wu, Desheng (Dash) & Lee, Chi-Guhn, 2010. "Stochastic DEA with ordinal data applied to a multi-attribute pricing problem," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1679-1688, December.
    9. Giada Spaccapanico Proietti & Mariagiulia Matteucci & Stefania Mignani & Bernard P. Veldkamp, 2024. "Chance-Constrained Automated Test Assembly," Journal of Educational and Behavioral Statistics, , vol. 49(1), pages 92-120, February.
    10. Guigues, Vincent & Juditsky, Anatoli & Nemirovski, Arkadi, 2021. "Constant Depth Decision Rules for multistage optimization under uncertainty," European Journal of Operational Research, Elsevier, vol. 295(1), pages 223-232.
    11. Bilsel, R. Ufuk & Ravindran, A., 2011. "A multiobjective chance constrained programming model for supplier selection under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1284-1300, September.
    12. Glover, Fred & Sueyoshi, Toshiyuki, 2009. "Contributions of Professor William W. Cooper in Operations Research and Management Science," European Journal of Operational Research, Elsevier, vol. 197(1), pages 1-16, August.
    13. Georgia Fargetta & Antonino Maugeri & Laura Scrimali, 2022. "A Stochastic Nash Equilibrium Problem for Medical Supply Competition," Journal of Optimization Theory and Applications, Springer, vol. 193(1), pages 354-380, June.
    14. Mahdi Takalloo & Changhyun Kwon, 2019. "On the Price of Satisficing in Network User Equilibria," Papers 1911.07914, arXiv.org.
    15. S. N. Gupta & A. K. Jain & Kanti Swarup, 1987. "Stochastic linear fractional programming with the ratio of independent Cauchy variates," Naval Research Logistics (NRL), John Wiley & Sons, vol. 34(2), pages 293-305, April.
    16. Zervopoulos, Panagiotis & Emrouznejad, Ali & Sklavos, Sokratis, 2019. "A Bayesian approach for correcting bias of data envelopment analysis estimators," MPRA Paper 91886, University Library of Munich, Germany.
    17. R. Caballero & E. Cerda & M. Muñoz & L. Rey, 2002. "Analysis and comparisons of some solution concepts for stochastic programming problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 10(1), pages 101-123, June.
    18. Longsheng Sun & Mark H. Karwan & Changhyun Kwon, 2018. "Generalized Bounded Rationality and Robust Multicommodity Network Design," Operations Research, INFORMS, vol. 66(1), pages 42-57, 1-2.
    19. Lin, Sheng-Wei & Lu, Wen-Min, 2024. "A comparison of chance-constrained data envelopment analysis, stochastic nonparametric envelopment of data and bootstrap method: A case study of cultural regeneration performance of cities," European Journal of Operational Research, Elsevier, vol. 316(3), pages 1179-1191.
    20. Hongmin Li & Stephen C. Graves & Woonghee Tim Huh, 2014. "Optimal Capacity Conversion for Product Transitions Under High Service Requirements," Manufacturing & Service Operations Management, INFORMS, vol. 16(1), pages 46-60, 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:jglopt:v:72:y:2018:i:4:d:10.1007_s10898-018-0664-8. 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.