When Nash Meets Stackelberg

Author:

Carvalho Margarida1ORCID,Dragotto Gabriele2ORCID,Feijoo Felipe3ORCID,Lodi Andrea4ORCID,Sankaranarayanan Sriram5ORCID

Affiliation:

1. CIRRELT and Département d’Informatique et de Recherche Opérationnelle, Université de Montréal, Montréal, Quebec H3T 1J4, Canada;

2. Department of Operations Research and Financial Engineering, Princeton University, Princeton, New Jersey 08544;

3. School of Industrial Engineering, Pontificia Universidad Católica de Valparaíso, Valparaíso 2340025, Chile;

4. Jacobs Technion-Cornell Institute, Cornell Tech and Technion – IIT, New York City, New York 10044;

5. Operations and Decision Sciences, Indian Institute of Management, Ahmedabad 380015, Gujarat, India

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 [Formula: see text]-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. This paper was accepted by Chung Piaw Teo, optimization. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.03418 .

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

Subject

Management Science and Operations Research,Strategy and Management

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3