随机对偶动态规划及其变体综述

IF 6.1 1区数学 Q1 MATHEMATICS, APPLIED

SIAM Review Pub Date : 2025-08-07 DOI:10.1137/23m1575093

Christian Füllner, Steffen Rebennack

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引用次数: 0

摘要

SIAM评论，第67卷，第3期，第415-539页，2025年8月。摘要。随机对偶动态规划（SDDP）是解决大规模多阶段随机规划的最先进的方法之一。自从大约30年前被引入来解决能源规划中的大规模多阶段随机线性规划问题以来，SDDP已被应用于多个领域的实际问题，并通过各种改进和增强得到了丰富，以解决更广泛的问题类别。我们从详细介绍SDDP开始，特别关注它的动机、复杂性和所需的假设。然后，我们提出并深入讨论了现有的改进以及当前的研究趋势，这些趋势允许减轻这些假设。

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Stochastic Dual Dynamic Programming and Its Variants: A Review

SIAM Review, Volume 67, Issue 3, Page 415-539, August 2025.
Abstract.We provide a tutorial-style review of stochastic dual dynamic programming (SDDP), one of the state-of-the-art solution methods for large-scale multistage stochastic programs. Since it was introduced about 30 years ago for solving large-scale multistage stochastic linear programming problems in energy planning, SDDP has been applied to practical problems from several fields and has been enriched by various improvements and enhancements to address broader problem classes. We begin with a detailed introduction to SDDP, with special focus on its motivation, complexity, and required assumptions. Then, we present and discuss in depth the existing enhancements as well as current research trends that allow for the alleviation of those assumptions.

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来源期刊

SIAM Review 数学-应用数学

CiteScore

16.90

自引率

0.00%

发文量

期刊介绍： Survey and Review feature papers that provide an integrative and current viewpoint on important topics in applied or computational mathematics and scientific computing. These papers aim to offer a comprehensive perspective on the subject matter. Research Spotlights publish concise research papers in applied and computational mathematics that are of interest to a wide range of readers in SIAM Review. The papers in this section present innovative ideas that are clearly explained and motivated. They stand out from regular publications in specific SIAM journals due to their accessibility and potential for widespread and long-lasting influence.