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Gauss–Seidel Method for Multi-leader–follower Games

Author

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  • Atsushi Hori

    (Nanzan University)

  • Masao Fukushima

    (Nanzan University)

Abstract

The multi-leader–follower game has many applications such as the bilevel structured market in which two or more enterprises, called leaders, have initiatives, and the other firms, called followers, observe the leaders’ decisions and then decide their own strategies. A special case of the game is the Stackelberg model, or the single-leader–follower game, which has been studied for many years. The Stackelberg game may be reformulated as a mathematical program with equilibrium constraints, which has also been studied extensively in recent years. On the other hand, the multi-leader–follower game may be formulated as an equilibrium problem with equilibrium constraints, in which each leader’s problem is an mathematical program with equilibrium constraints. However, finding an equilibrium point of an equilibrium problem with equilibrium constraints is much more difficult than solving a single mathematical program with equilibrium constraints, because each leader’s problem contains those variables which are common to other players’ problems. Moreover, the constraints of each leader’s problem depend on the other rival leaders’ strategies. In this paper, we propose a Gauss–Seidel type algorithm with a penalty technique for solving an equilibrium problem with equilibrium constraints associated with the multi-leader–follower game, and then suggest a refinement procedure to obtain more accurate solutions. We discuss convergence of the algorithm and report some numerical results to illustrate the behavior of the algorithm.

Suggested Citation

  • Atsushi Hori & Masao Fukushima, 2019. "Gauss–Seidel Method for Multi-leader–follower Games," Journal of Optimization Theory and Applications, Springer, vol. 180(2), pages 651-670, February.
  • Handle: RePEc:spr:joptap:v:180:y:2019:i:2:d:10.1007_s10957-018-1391-5
    DOI: 10.1007/s10957-018-1391-5
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    References listed on IDEAS

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    1. Holger Scheel & Stefan Scholtes, 2000. "Mathematical Programs with Complementarity Constraints: Stationarity, Optimality, and Sensitivity," Mathematics of Operations Research, INFORMS, vol. 25(1), pages 1-22, February.
    2. Ming Hu & Masao Fukushima, 2011. "Variational Inequality Formulation of a Class of Multi-Leader-Follower Games," Journal of Optimization Theory and Applications, Springer, vol. 151(3), pages 455-473, December.
    3. Yihsu Chen & Benjamin Hobbs & Sven Leyffer & Todd Munson, 2006. "Leader-Follower Equilibria for Electric Power and NO x Allowances Markets," Computational Management Science, Springer, vol. 3(4), pages 307-330, September.
    4. Ming Hu & Masao Fukushima, 2012. "Smoothing approach to Nash equilibrium formulations for a class of equilibrium problems with shared complementarity constraints," Computational Optimization and Applications, Springer, vol. 52(2), pages 415-437, June.
    5. Jong-Shi Pang & Masao Fukushima, 2005. "Quasi-variational inequalities, generalized Nash equilibria, and multi-leader-follower games," Computational Management Science, Springer, vol. 2(1), pages 21-56, January.
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    Cited by:

    1. Atsushi Hori & Daisuke Tsuyuguchi & Ellen H. Fukuda, 2024. "A Method for Multi-Leader–Multi-Follower Games by Smoothing the Followers’ Response Function," Journal of Optimization Theory and Applications, Springer, vol. 203(1), pages 305-335, October.

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