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Integrating Prediction/Estimation and Optimization with Applications in Operations Management
10 references·2 citing·41 second hop
Integrating Prediction/Estimation and Optimization with Applications in Operations Management (2022)Integrating Prediction/Estimation and Opt…Smart “Predict, then Optimize” (2021)Smart “Predict, then Optimize”Machine Learning: Algorithms, Real-World Applications and Research Directions (2021)Machine Learning: Algorithms,…Data‐Driven Newsvendor Problems Regularized by a Profit Risk Constraint (2021)Data‐Driven Newsvendor Proble…Quantile forecasting and data-driven inventory management under nonstationary demand (2019)Quantile forecasting and data…Prescriptive Analytics for Flexible Capacity Management (2019)Prescriptive Analytics for Fl…From Predictive to Prescriptive Analytics (2019)From Predictive to Prescripti…Applying deep learning to the newsvendor problem (2019)Applying deep learning to the…The Big Data Newsvendor: Practical Insights from Machine Learning (2018)The Big Data Newsvendor: Prac…Introduction to Stochastic Programming (2011)Introduction to Stochastic Pr…Linear Programming under Uncertainty (1955)Linear Programming under Unce…Properties of Suboptimality Loss (2025)Properties of Suboptimality L…Contextual Stochastic Optimization for Omnichannel Multicourier Order Fulfillment Under Delivery Time Uncertainty (2025)Contextual Stochastic Optimiz…A Stochastic Approximation Method (1951)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Optimization of conditional value-at-risk (2000)Impact of business analytics and enterprise systems on managerial accounting (2017)Frameworks and Results in Distributionally Robust Optimization (2022)Analysis of Inventory Systems. (1964)Time Series Analysis: Forecasting and Control. (1978)Practical Bayesian Optimization of Machine Learning Algorithms (2012)A data-driven newsvendor problem: From data to decision (2019)A Deep Q-Network for the Beer Game: Deep Reinforcement Learning for Inventory Optimization (2021)A survey of contextual optimization methods for decision-making under uncertainty (2024)Dynamic Version of the Economic Lot Size Model (1958)Dynamic Version of the Economic Lot Size Model (2004)Forecasting: theory and practice (2022)From natural language to simulations: applying AI to automate simulation modelling of logistics systems (2023)Intelligent digital twin (iDT) for supply chain stress-testing, resilience, and viability (2023)A Single-Item Inventory Model for a Nonstationary Demand Process (1999)The single-period (news-vendor) problem: literature review and suggestions for future research (1999)Wiley encyclopedia of operations research and management science (2011)A Data-Based Model Predictive Decision Support System for Inventory Management in Hospitals (2020)An end-to-end deep learning model for solving data-driven newsvendor problem with accessibility to textual review data (2023)On the use of machine learning in supply chain management: a systematic review (2023)Studies in Mathematical Theory of Inventory and Production (1959)The Distribution Free Newsboy Problem: Review and Extensions (1993)Lectures on Stochastic Programming (2009)Automatic Time Series Forecasting: The forecast Package for R (2008)Forecasting Time Series With Complex Seasonal Patterns Using Exponential Smoothing (2011)Deep Learning for Commodity Procurement: Nonlinear Data-Driven Optimization of Hedging Decisions (2022)Dynamic optimization with side information (2022)The role of optimization in some recent advances in data-driven decision-making (2022)The economic implications of corporate financial reporting (2005)Developing Operations Management Data Analytics (2022)Risk preferences, newsvendor orders and supply chain coordination using the Mean-CVaR model (2024)Robust optimization approaches in inventory management: Part A—the survey (2024)Conditional value-at-risk for general loss distributions (2002)Theory and Applications of Robust Optimization (2011)Data Science and Analytics: An Overview from Data-Driven Smart Computing, Decision-Making and Applications Perspective (2021)Future smart cities: requirements, emerging technologies, applications, challenges, and future aspects (2022)Smart City Data Science: Towards data-driven smart cities with open research issues (2022)Optimization under uncertainty: state-of-the-art and opportunities (2003)Stochastic Programming (2010)
this work references cited by second hop

References

  • 2011Introduction to Stochastic Programming6,490 cited
  • 2021Machine Learning: Algorithms, Real-World Applications and Research Directions5,577 cited
  • 1955Linear Programming under Uncertainty1,232 cited
  • 2021Smart “Predict, then Optimize”880 cited
  • 2019From Predictive to Prescriptive Analytics868 cited
  • 2018The Big Data Newsvendor: Practical Insights from Machine Learning531 cited
  • 2019Applying deep learning to the newsvendor problem163 cited
  • 2019Quantile forecasting and data-driven inventory management under nonstationary demand59 cited
  • 2019Prescriptive Analytics for Flexible Capacity Management53 cited
  • 2021Data‐Driven Newsvendor Problems Regularized by a Profit Risk Constraint49 cited

Cited by

  • 2025Contextual Stochastic Optimization for Omnichannel Multicourier Order Fulfillment Under Delivery Time Uncertainty8 cited
  • 2025Properties of Suboptimality Loss0 cited

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