When Nash Meets Stackelberg

Carvalho; M.; Dragotto; G.; Feijoo; F.; Lodi; A.; Sankaranarayanan; S.

Keywords: algorithmic game theory; bilevel optimization; integer programming; Stackelberg game

Abstract

This article introduces a class of Nash games among Stackelberg players (NASPs), namely, a class of simultaneous noncooperative games where the players solve sequential Stackelberg games. Specifically, each player solves a Stackelberg game where a leader optimizes a (parametrized) linear objective function subject to linear constraints, whereas its followers solve convex quadratic problems subject to the standard optimistic assumption. Although we prove that deciding if a NASP instance admits a Nash equilibrium is generally a ?p2-hard decision problem, we devise two exact and computationally efficient algorithms to compute and select Nash equilibria or certify that no equilibrium exists. We use NASPs to model the hierarchical interactions of international energy markets where climate change aware regulators oversee the operations of profit-driven energy producers. By combining real-world data with our models, we find that Nash equilibria provide informative, and often counterintuitive, managerial insights for market regulators. © 2023 INFORMS.

Más información

Título según WOS: ID WOS:001132637800001 Not found in local WOS DB
Título según SCOPUS: When Nash Meets Stackelberg
Título de la Revista: Management Science
Volumen: 70
Número: 10
Editorial: INFORMS Inst.for Operations Res.and the Management Sciences
Fecha de publicación: 2024
Página de inicio: 7308
Página final: 7324
Idioma: English
DOI:

10.1287/mnsc.2022.03418

Notas: ISI, SCOPUS