An inexact algorithm for stochastic variational inequalities

IF 0.8 4区管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Letters Pub Date : 2024-01-01 DOI:10.1016/j.orl.2023.107064

Emelin L. Buscaglia , Pablo A. Lotito , Lisandro A. Parente

引用次数: 0

Abstract

We present a new Progressive Hedging Algorithm to solve Stochastic Variational Inequalities in the formulation introduced by Rockafellar and Wets in 2017, allowing the generated subproblems to be approximately solved with an implementable tolerance condition. Our scheme is based on Hybrid Inexact Proximal Point methods and generalizes the exact algorithm developed by Rockafellar and Sun in 2019, providing stronger convergence results. We also show some numerical experiments in two-stage Nash games.

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随机变分不等式的非精确算法

我们提出了一种新的渐进对冲算法，用于求解 Rockafellar 和 Wets 于 2017 年提出的随机变分不等式，允许生成的子问题在可实施的容差条件下近似求解。我们的方案基于混合非精确近端点方法，并对 Rockafellar 和 Sun 于 2019 年开发的精确算法进行了概括，提供了更强的收敛结果。我们还展示了一些两阶段纳什博弈的数值实验。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Operations Research Letters 管理科学-运筹学与管理科学

CiteScore

2.10

自引率

9.10%

发文量

111

审稿时长

83 days

期刊介绍： Operations Research Letters is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. Apart from a limitation to eight journal pages, quality, originality, relevance and clarity are the only criteria for selecting the papers to be published. ORL covers the broad field of optimization, stochastic models and game theory. Specific areas of interest include networks, routing, location, queueing, scheduling, inventory, reliability, and financial engineering. We wish to explore interfaces with other fields such as life sciences and health care, artificial intelligence and machine learning, energy distribution, and computational social sciences and humanities. Our traditional strength is in methodology, including theory, modelling, algorithms and computational studies. We also welcome novel applications and concise literature reviews.