Local Stackelberg equilibrium seeking in generalized aggregative games

Journal Article (2022)
Author(s)

Filippo Fabiani (University of Oxford)

Mohammad Amin Tajeddini (University of Tehran)

Hamed Kebriaei (University of Tehran)

S. Grammatico (TU Delft - Team Sergio Grammatico, TU Delft - Team Bart De Schutter)

Research Group
Team Sergio Grammatico
Copyright
© 2022 Filippo Fabiani, Mohammad Amin Tajeddini, Hamed Kebriaei, S. Grammatico
DOI related publication
https://doi.org/10.1109/TAC.2021.3077874
More Info
expand_more
Publication Year
2022
Language
English
Copyright
© 2022 Filippo Fabiani, Mohammad Amin Tajeddini, Hamed Kebriaei, S. Grammatico
Research Group
Team Sergio Grammatico
Issue number
2
Volume number
67
Pages (from-to)
965-970
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

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).

Files

Local_Stackelberg_Equilibrium_... (pdf)
(pdf | 0.476 Mb)
- Embargo expired in 01-07-2023
License info not available