Exact solving approach to moment problems with nonnegative Chebyshev ambiguity sets

IF 0.9 4区管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Letters Pub Date : 2025-07-30 DOI:10.1016/j.orl.2025.107349

Jiayi Guo , Hao Qiu , Zhen Wang , Zizhuo Wang , Xinxin Zhang

引用次数: 0

Abstract

We study the moment problem with nonnegative Chebyshev ambiguity set (MPNC), which is foundational to distributionally robust optimization (DRO) and has applications in inventory, pricing, and portfolio selection problems. While univariate MPNC is well-studied, bivariate/multivariate MPNC lacks analytical solutions. We characterize bivariate MPNC's optimal support for piecewise-linear objectives, propose an exact numerical method, and derive closed-form solutions for two instances. We apply our result to a DRO newsvendor problem and derive interesting managerial insights.

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非负Chebyshev模糊集矩问题的精确求解方法

本文研究了具有非负Chebyshev模糊集（MPNC）的矩问题，该问题是分布鲁棒优化（DRO）的基础，在库存、定价和投资组合选择问题中具有广泛的应用。虽然单变量MPNC研究得很好，但双变量/多变量MPNC缺乏解析解。我们描述了二元MPNC对分段线性目标的最优支持，提出了一种精确的数值方法，并推导了两个实例的封闭形式解。我们将我们的结果应用于DRO报贩问题，并获得有趣的管理见解。

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.