A Method for Multi-Leader–Multi-Follower Games by Smoothing the Followers’ Response Function

The multi-leader–multi-follower game (MLMFG) involves two or more leaders and followers and serves as a generalization of the Stackelberg game and the single-leader–multi-follower game. Although MLMFG covers wide range of real-world applications, its research is still sparse. Notably, fundamental so...

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Vydáno v:Journal of optimization theory and applications Ročník 203; číslo 1; s. 305 - 335
Hlavní autoři: Hori, Atsushi, Tsuyuguchi, Daisuke, Fukuda, Ellen H.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.10.2024
Springer Nature B.V
Témata:
Applications of Mathematics
Calculus of Variations and Optimal Control; Optimization
Complex variables
Engineering
Equilibrium
Game theory
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Optimization
Response functions
Smoothing
Theory of Computation
Equilibrium problem with equilibrium constraints
Smoothing approximation
Nash equilibrium problem
Bilevel optimization
91A65
91A10
90C33
Multi-leader–follower game
ISSN:0022-3239, 1573-2878
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Shrnutí:The multi-leader–multi-follower game (MLMFG) involves two or more leaders and followers and serves as a generalization of the Stackelberg game and the single-leader–multi-follower game. Although MLMFG covers wide range of real-world applications, its research is still sparse. Notably, fundamental solution methods for this class of problems remain insufficiently established. A prevailing approach is to recast the MLMFG as an equilibrium problem with equilibrium constraints (EPEC) and solve it using a solver. Meanwhile, interpreting the solution to the EPEC in the context of MLMFG may be complex due to shared decision variables among all leaders, followers’ strategies that each leader can unilaterally change, but the variables are essentially controlled by followers. To address this issue, we introduce a response function of followers’ noncooperative game that is a function with leaders’ strategies as a variable. Employing this approach allows the MLMFG to be solved as a single-level differentiable variational inequality using a smoothing scheme for the followers’ response function. We also demonstrate that the sequence of solutions to the smoothed variational inequality converges to a stationary equilibrium of the MLMFG. Finally, we illustrate the behavior of the smoothing method by numerical experiments.
Bibliografie:ObjectType-Article-1
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ISSN:0022-3239
1573-2878
DOI:10.1007/s10957-024-02506-2