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arXiv · 2006.03916

Local Stackelberg equilibrium seeking in generalized aggregative games

Filippo Fabiani·Mohammad Amin Tajeddini·Hamed Kebriaei·Sergio Grammatico
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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 involving a hierarchical instance of the charging coordination of Plug-in Electric Vehicles (PEVs).

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Filippo Fabiani, Mohammad Amin Tajeddini, Hamed Kebriaei, Sergio Grammatico. 2020-06-06. Local Stackelberg equilibrium seeking in generalized aggregative games. https://doi.org/10.1109/tac.2021.3077874

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