Solving policy design problems: Alternating direction method of multipliers-based methods for structured inverse variational inequalities

Yaning Jiang, Xingju Cai and Deren Han

European Journal of Operational Research, 2020, vol. 280, issue 2, 417-427

Abstract: Inverse variational inequalities have broad applications in various disciplines, and some of them have very appealing structures. There are several algorithms (e.g., proximal point algorithms and projection-type algorithms) for solving the inverse variational inequalities in general settings, while few of them have fully exploited the special structures. In this paper, we consider a class of inverse variational inequalities that has a separable structure and linear constraints, which has its root in spatial economic equilibrium problems. To design an efficient algorithm, we develop an alternating direction method of multipliers (ADMM) based method by utilizing the separable structure. Under some mild assumptions, we prove its global convergence. We propose an improved variant that makes the subproblems much easier and derive the convergence result under the same conditions. Finally, we present the preliminary numerical results to show the capability and efficiency of the proposed methods.

Keywords: Convex programming; Inverse variational inequalities; Alternating direction method of multipliers; Monotone mapping (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:280:y:2020:i:2:p:417-427

DOI: 10.1016/j.ejor.2019.05.044

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