Yijie Wang – Optimization Online

Distributionally Robust Optimization via Targeted Integral Probability Metrics for General Data Processes

Published: 2026/05/28

Optimization in Data Science, Robust Optimization, Stochastic Programming Contextual optimization, corrupted and missing data, curse of dimensionality, distributionally robust optimization, heavy-tailed distributions, integral probability metrics, markovian data

Distributionally robust optimization (DRO) has been successful in addressing decision-making problems under uncertainty when the underlying distribution is unknown. Existing data-driven DRO frameworks, however, often impose restrictive assumptions on the data-generating process. We propose a new DRO framework based on targeted integral probability metrics. The ambiguity set is defined directly through the loss functions induced … Read more

Data-Driven Contextual Optimization with Gaussian Mixtures: Flow-Based Generalization, Robust Models, and Multistage Extensions

Published: 2025/08/16, Updated: 2025/09/16

YoungChul Yoon

Grani A. Hanasusanto

Yijie Wang

Robust Optimization, Stochastic Programming contextual stochastic optimization, data-driven dynamic programming, distributionally robust optimization, gaussian mixture models, multistage stochastic programming, normalizing flows

Contextual optimization enhances decision quality by leveraging side information to improve predictions of uncertain parameters. However, existing approaches face significant challenges when dealing with multimodal or mixtures of distributions. The inherent complexity of such structures often precludes an explicit functional relationship between the contextual information and the uncertain parameters, limiting the direct applicability of parametric … Read more