A survey of contextual optimization methods for decision-making under uncertainty

U Sadana, A Chenreddy, E Delage, A Forel… - European Journal of …, 2024 - Elsevier
Recently there has been a surge of interest in operations research (OR) and the machine
learning (ML) community in combining prediction algorithms and optimization techniques to …

Predict-then-calibrate: A new perspective of robust contextual lp

C Sun, L Liu, X Li - Advances in Neural Information …, 2023 - proceedings.neurips.cc
Contextual optimization, also known as predict-then-optimize or prescriptive analytics,
considers an optimization problem with the presence of covariates (context or side …

Data-driven conditional robust optimization

AR Chenreddy, N Bandi… - Advances in Neural …, 2022 - proceedings.neurips.cc
In this paper, we study a novel approach for data-driven decision-making under uncertainty
in the presence of contextual information. Specifically, we solve this problem from a …

Integrated conditional estimation-optimization

M Qi, P Grigas, ZJM Shen - arxiv preprint arxiv:2110.12351, 2021 - arxiv.org
Many real-world optimization problems involve uncertain parameters with probability
distributions that can be estimated using contextual feature information. In contrast to the …

[HTML][HTML] A bilevel framework for decision-making under uncertainty with contextual information

MA Muñoz, S Pineda, JM Morales - Omega, 2022 - Elsevier
In this paper, we propose a novel approach for data-driven decision-making under
uncertainty in the presence of contextual information. Given a finite collection of …

Fast rates for contextual linear optimization

Y Hu, N Kallus, X Mao - Management Science, 2022 - pubsonline.informs.org
Incorporating side observations in decision making can reduce uncertainty and boost
performance, but it also requires that we tackle a potentially complex predictive relationship …

Data‐driven research in retail operations—A review

M Qi, HY Mak, ZJM Shen - Naval Research Logistics (NRL), 2020 - Wiley Online Library
We review the operations research/management science literature on data‐driven methods
in retail operations. This line of work has grown rapidly in recent years, thanks to the …