On Distributionally Robust Multistage Convex Optimization: New Algorithms and Complexity Analysis
Year: 2026
Type: article
Abstract: . This paper presents an algorithmic study and complexity analysis for solving distributionally robust multistage convex optimization (DR-MCO) problems. Our main contribution is a novel nonconsecutive dual dynamic programming (NDDP) algorithm which explores different stages in an adaptive fashion. In contrast with the usual consecutive dual dynamic programming algorithm, we show that NDDP reduces the subproblem complexity from quadratic to linear dependency on the number of stages. Two different DR-MCO examples are also presented to show the efficiency and effectiveness of the proposed NDDP algorithm.
Source: SIAM Journal on Optimization
DOI: 10.1137/25m1761690
Authors: Shixuan Zhang, Xu Andy Sun
Institutions: Texas A&M University, Massachusetts Institute of Technology
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W3093435276