mlsanityData to 14 Oct 2026

A Survey of Contextual Optimization Methods for Decision Making under Uncertainty

arXiv 2306.10374 ↗First posted 17 Jun 2023math.OC cs.LGcited by 82

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Abstract (arXiv)

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 solve decision-making problems in the face of uncertainty. This gave rise to the field of contextual optimization, under which data-driven procedures are developed to prescribe actions to the decision-maker that make the best use of the most recently updated information. A large variety of models and methods have been presented in both OR and ML literature under a variety of names, including data-driven optimization, prescriptive optimization, predictive stochastic programming, policy optimization, (smart) predict/estimate-then-optimize, decision-focused learning, (task-based) end-to-end learning/forecasting/optimization, etc. Focusing on single and two-stage stochastic programming problems, this review article identifies three main frameworks for learning policies from data and discusses their strengths and limitations. We present the existing models and methods under a uniform notation and terminology and classify them according to the three main frameworks identified. Our objective with this survey is to both strengthen the general understanding of this active field of research and stimulate further theoretical and algorithmic advancements in integrating ML and stochastic programming.

Key facts. Cited by 82 papers in the map (data through 14 Oct 2026). Builds on 88 of its 189 references that are in the map. First posted on arXiv 17 Jun 2023.

Builds on

88 of 189 references.

References · 88

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38 more
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Citing papers per year: 2023: 9; 2024: 16; 2025: 22; 2026: 35.

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  1. 2023Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunitiescited by 130
  2. 2023Conformal Contextual Robust Optimizationcited by 25
  3. 2024End-to-end Conditional Robust Optimizationcited by 17
  4. 2024Decision-Focused Learning with Directional Gradientscited by 16
  5. 2023Contextual Stochastic Bilevel Optimizationcited by 14
  6. 2024Utility-Directed Conformal Prediction: A Decision-Aware Framework for Actionable Uncertainty Quantificationcited by 13
  7. 2023Score Function Gradient Estimation to Widen the Applicability of Decision-Focused Learningcited by 11
  8. 2023TaskMet: Task-Driven Metric Learning for Model Learningcited by 11
  9. 2025Conformal Risk Training: End-to-End Optimization of Conformal Risk Controlcited by 11
  10. 2025What Data Enables Optimal Decisions? An Exact Characterization for Linear Optimizationcited by 9
  11. 2023CaVE: A Cone-Aligned Approach for Fast Predict-then-optimize with Binary Linear Programscited by 8
  12. 2024Differentiable Distributionally Robust Optimization Layerscited by 8
38 more
  1. 2024Towards a Systems Theory of Algorithmscited by 7
  2. 2025Structured Reinforcement Learning for Combinatorial Decision-Makingcited by 7
  3. 2023Robust Losses for Decision-Focused Learningcited by 5
  4. 2025Enhanced Route Planning with Calibrated Uncertainty Setcited by 5
  5. 2024A Functional Model Method for Nonconvex Nonsmooth Conditional Stochastic Optimizationcited by 4
  6. 2025Primal-dual algorithm for contextual stochastic combinatorial optimizationcited by 4
  7. 2025Online Decision-Focused Learningcited by 4
  8. 2026Decision-Focused Learning via Tangent-Space Projection of Prediction Errorcited by 4
  9. 2026Regret Equals Covariance: A Closed-Form Characterization for Stochastic Optimizationcited by 4
  10. 2023Learning Lagrangian Multipliers for the Travelling Salesman Problemcited by 3
  11. 2024Generalization Bounds of Surrogate Policies for Combinatorial Optimization Problemscited by 3
  12. 2024Regularization for Adversarial Robust Learningcited by 3
  13. 2026Combinatorial Optimization Augmented Machine Learningcited by 3
  14. 2026A Solver-Free Training Method for Predict-then-Optimizecited by 3
  15. 2024Forecasting Outside the Box: Application-Driven Optimal Pointwise Forecasts for Stochastic Optimizationcited by 2
  16. 2025Sufficient Decision Proxies for Decision-Focused Learningcited by 2
  17. 2025Learning with Local Search MCMC Layerscited by 2
  18. 2025Smart Surrogate Losses for Contextual Stochastic Linear Optimization with Robust Constraintscited by 2
  19. 2025Minimizing Surrogate Losses for Decision-Focused Learning using Differentiable Optimizationcited by 2
  20. 2025Bi-Level Decision-Focused Causal Learning for Large-Scale Marketing Optimization: Bridging Observational and Experimental Datacited by 2
  21. 2026VeriSimpl: Robust Optimization Modeling from Natural Language using Simplification-based Verificationcited by 2
  22. 2023Learning Deterministic Surrogates for Robust Convex QCQPscited by 1
  23. 2024Contextual Stochastic Vehicle Routing with Time Windowscited by 1
  24. 2024Generative Conditional Distributions by Neural (Entropic) Optimal Transportcited by 1
  25. 2024Feature-Based Interpretable Surrogates for Optimizationcited by 1
  26. 2024DistrictNet: Decision-aware learning for geographical districtingcited by 1
  27. 2025Decision-aware training of spatiotemporal forecasting models to select a top K subset of sites for interventioncited by 1
  28. 2026Learning Decision-Sufficient Representations for Linear Optimizationcited by 1
  29. 2026Decision-Focused Federated Learning Under Heterogeneous Objectives and Constraintscited by 1
  30. 2026Quantum End-to-End Learning for Contextual Combinatorial Optimizationcited by 1
  31. 2026Decision-Focused On-Policy Learning for Contextual Linear Optimization with Partial Feedbackcited by 1
  32. 2026Decision-Focused Learning: When and Why Traditional Prediction Models Failcited by 1
  33. 2026End-to-End Fairness Optimization with Fair Decision-Focused Learningcited by 1
  34. 2024CF-OPT: Counterfactual Explanations for Structured Predictioncited by 0
  35. 2024Evaluation of Prosumer Networks for Peak Load Management in Iran: A Distributed Contextual Stochastic Optimization Approachcited by 0
  36. 2024The Differentiable Feasibility Pumpcited by 0
  37. 2025Contextual Scenario Generation for Two-Stage Stochastic Programmingcited by 0
  38. 2025Preference Elicitation for Multi-objective Combinatorial Optimization with Active Learning and Maximum Likelihood Estimationcited by 0

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