Local Stackelberg equilibrium seeking in generalized aggregative games

Local Stackelberg equilibrium seeking in generalized aggregative games

Fabiani, Filippo (University of Oxford)
Tajeddini, Mohammad Amin (University of Tehran)
Kebriaei, Hamed (University of Tehran)
Grammatico, S. (TU Delft Team Bart De Schutter; TU Delft Team Sergio Grammatico)

2022

We propose a two-layer, semi-decentralized algorithm to compute a local solution to the Stackelberg equilibrium problem in aggregative games with coupling constraints. Specifically, we focus on a single-leader, multiple follower problem, and after equivalently recasting the Stackelberg game as a mathematical program with complementarity constraints (MPCC), we iteratively convexify a regularized version of the MPCC as inner problem, whose solution generates a sequence of feasible descent directions for the original MPCC. Thus, by pursuing a descent direction at every outer iteration, we establish convergence to a local Stackelberg equilibrium. Finally, the proposed algorithm is tested on a numerical case study, a hierarchical instance of the charging coordination problem of Plug-in Electric Vehicles (PEVs).

Approximation algorithms
Convergence
Cost function
Couplings
game theory
Games
hierarchical systems
optimization
Stackelberg equilibrium
Standards
Wireless networks

http://resolver.tudelft.nl/uuid:097e50d8-e151-4221-bcc3-bb34d1c6ac89

https://doi.org/10.1109/TAC.2021.3077874

2023-07-01

0018-9286

IEEE Transactions on Automatic Control, 67 (2), 965-970

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

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journal article

© 2022 Filippo Fabiani, Mohammad Amin Tajeddini, Hamed Kebriaei, S. Grammatico