Optimal Robust Policy for Feature-Based Newsvendor
Published Online:2 Jun 2023https://doi.org/10.1287/mnsc.2023.4810
References
- (2021) Generalization bounds for (Wasserstein) robust optimization. Adv. Neural Inform. Processing Systems 34:10382–10392.Google Scholar
- (2019) The big data newsvendor: Practical insights from machine learning. Oper. Res. 67(1):90–108.Link, Google Scholar
- (2019) Dynamic procurement of new products with covariate information: The residual tree method. Manufacturing Service Oper. Management 21(4):798–815.Link, Google Scholar
- (2015) Data-driven stochastic programming using phi-divergences. The Operations Research Revolution (INFORMS, Catonsville, MD), 1–19.Link, Google Scholar
- (2009) Robust Optimization, vol. 28 (Princeton University Press, Princeton, NJ), 365–370.Crossref, Google Scholar
- (2013) Robust solutions of optimization problems affected by uncertain probabilities. Management Sci. 59(2):341–357.Link, Google Scholar
- (2015) Design of near optimal decision rules in multistage adaptive mixed-integer optimization. Oper. Res. 63(3):610–627.Link, Google Scholar
- (2012) On the power and limitations of affine policies in two-stage adaptive optimization. Math. Programming 134(2):491–531.Crossref, Google Scholar
- (2020) From predictive to prescriptive analytics. Management Sci. 66(3):1025–1044.Link, Google Scholar
- (2022) Data-driven optimization: A reproducing kernel Hilbert space approach. Oper. Res. 70(1):454–471.Link, Google Scholar
- (2010) Optimality of affine policies in multistage robust optimization. Math. Oper. Res. 35(2):363–394.Link, Google Scholar
- (2011) A hierarchy of near-optimal policies for multistage adaptive optimization. IEEE Trans. Automatic Control 56(12):2809–2824.Crossref, Google Scholar
- (2023) Dynamic optimization with side information. Eur. J. Oper. Res. 304(2):634–651.Crossref, Google Scholar
- (2016) Robust newsvendor problem with autoregressive demand. Comput. Oper. Res. 68:123–133.Crossref, Google Scholar
- (2008) A linear decision-based approximation approach to stochastic programming. Oper. Res. 56(2):344–357.Link, Google Scholar
- (2021) Regret in the newsvendor model with demand and yield randomness. Production Oper. Management 30(11):4176–4197.Crossref, Google Scholar
- (2021) On the heavy-tail behavior of the distributionally robust newsvendor. Oper. Res. 69(4):1077–1099.Link, Google Scholar
- (2019) Generalization bounds in the predict-then-optimize framework. Adv. Neural Inform. Processing Systems 32:14412–14421.Google Scholar
- (2021) On the optimality of affine policies for budgeted uncertainty sets. Math. Oper. Res. 46(2):674–711.Link, Google Scholar
- (2022) Smart “predict, then optimize.” Management Sci. 68(1):9–26.Link, Google Scholar
- (2022) Distributionally robust stochastic programs with side information based on trimmings. Math. Programming 195(1–2):1069–1105.Crossref, Google Scholar
- (2021) Data-driven feature-based newsvendor: A distributionally robust approach. Preprint, submitted July 15, https://dx.doi.org/10.2139/ssrn.3885663.Google Scholar
- (1993) The distribution free newsboy problem: Review and extensions. J. Oper. Res. Soc. 44(8):825–834.Crossref, Google Scholar
- (2001) Minimax analysis for finite-horizon inventory models. IIE Trans. 33(10):861–874.Crossref, Google Scholar
- (2022) Finite-sample guarantees for Wasserstein distributionally robust optimization: Breaking the curse of dimensionality. Oper. Res. Forthcoming.Link, Google Scholar
- (2022) Distributionally robust stochastic optimization with Wasserstein distance. Math. Oper. Res. 48(2):603–655.Link, Google Scholar
- (2022) Wasserstein distributionally robust optimization and variation regularization. Oper. Res. Forthcoming.Link, Google Scholar
- (2021) On the Optimality of Affine Decision Rules in Robust and Distributionally Robust Optimization (Optimization Online).Google Scholar
- (2014) A risk-and ambiguity-averse extension of the max-min newsvendor order formula. Oper. Res. 62(3):535–542.Link, Google Scholar
- (2015a) K-adaptability in two-stage robust binary programming. Oper. Res. 63(4):877–891.Link, Google Scholar
- (2016) K-adaptability in two-stage distributionally robust binary programming. Oper. Res. Lett. 44(1):6–11.Crossref, Google Scholar
- (2015b) Distributionally robust multi-item newsvendor problems with multimodal demand distributions. Math. Programming 152(1):1–32.Crossref, Google Scholar
- (2010) Nonparametric density estimation for stochastic optimization with an observable state variable. Adv. Neural Inform. Processing Systems 23:820–828.Google Scholar
- (2022) Fast rates for contextual linear optimization. Management Sci. 68(6):4236–4245.Link, Google Scholar
- (2013) Supermodularity and affine policies in dynamic robust optimization. Oper. Res. 61(4):941–956.Link, Google Scholar
- (2022) Stochastic optimization forests. Management Sci. 69(4):1975–1994.Link, Google Scholar
- (2020a) Data-Driven Sample Average Approximation with Covariate Information (Optimization Online).Google Scholar
- (2020b) Residuals-based distributionally robust optimization with covariate information. Preprint, submitted December 2, https://arxiv.org/abs/2012.01088.Google Scholar
- (2019) Wasserstein distributionally robust optimization: Theory and applications in machine learning. Operations Research & Management Science in the Age of Analytics (INFORMS, Catonsville, MD), 130–166.Link, Google Scholar
- (2012) Newsvendor-type models with decision-dependent uncertainty. Math. Methods Oper. Res. 76(2):189–221.Crossref, Google Scholar
- (2020) A data-driven distributionally robust newsvendor model with a Wasserstein ambiguity set. J. Oper. Res. Soc. 72(8):1879–1897.Crossref, Google Scholar
- (2005) A practical inventory control policy using operational statistics. Oper. Res. Lett. 33(4):341–348.Crossref, Google Scholar
- (2020) Decision-driven regularization: Harmonizing the predictive and prescriptive. Preprint, submitted June 17, https://dx.doi.org/10.2139/ssrn.3623006.Google Scholar
- (2004) Distance-based classification with Lipschitz functions. J. Machine Learn. Res. 5:669–695.Google Scholar
- (2022) A practical end-to-end inventory management model with deep learning. Management Sci. 69(2):759–773.Google Scholar
- (2018) Data-driven distributionally robust optimization using the Wasserstein metric: Performance guarantees and tractable reformulations. Math. Programming 171(1):115–166.Crossref, Google Scholar
- (2018) Asymmetry and ambiguity in newsvendor models. Management Sci. 64(7):3146–3167.Link, Google Scholar
- (2020) Applying deep learning to the newsvendor problem. IISE Trans. 52(4):444–463.Crossref, Google Scholar
- Pentaho (2008) Foodmart’s database tables. Accessed January 1, 2021, http://pentaho.dlpage.phi-integration.com/mondrian/mysql-foodmart-database.Google Scholar
- (2008) Regret in the newsvendor model with partial information. Oper. Res. 56(1):188–203.Link, Google Scholar
- (2016) Multistage adjustable robust mixed-integer optimization via iterative splitting of the uncertainty set. INFORMS J. Comput. 28(3):553–574.Link, Google Scholar
- (2019a) Controlling risk and demand ambiguity in newsvendor models. Eur. J. Oper. Res. 279(3):854–868.Crossref, Google Scholar
- (2019b) Identifying effective scenarios in distributionally robust stochastic programs with total variation distance. Math. Programming 173(1):393–430.Crossref, Google Scholar
- (1958) A Min-Max Solution of an Inventory Problem (RAND Corporation, Santa Monica, CA).Google Scholar
- (2010) Robust approximation to multiperiod inventory management. Oper. Res. 58(3):583–594.Link, Google Scholar
- (2019) Regularization via mass transportation. J. Machine Learn. Res. 20(103):1–68.Google Scholar
- (2014) Lectures on Stochastic Programming: Modeling and Theory (SIAM, Philadelphia).Crossref, Google Scholar
- (1968) A two-dimensional interpolation function for irregularly spaced data. Proc. 23rd ACM National Conf., 517–524.Google Scholar
- (2021) On data-driven prescriptive analytics with side information: A regularized Nadaraya–Watson approach. Preprint, submitted October 10, https://arxiv.org/abs/2110.04855.Google Scholar
- (2021) A nonparametric algorithm for optimal stopping based on robust optimization. Preprint, submitted March 4, https://arxiv.org/abs/2103.03300.Google Scholar
- (2019) K-adaptability in two-stage mixed-integer robust optimization. Math. Programming Comput. 12:193–224.Crossref, Google Scholar
- (2001) Analysis of a forecasting-production-inventory system with stationary demand. Management Sci. 47(9):1268–1281.Link, Google Scholar
- (2016) Likelihood robust optimization for data-driven problems. Comput. Management Sci. 13(2):241–261.Crossref, Google Scholar
- (2021) Time (in) consistency of multistage distributionally robust inventory models with moment constraints. Eur. J. Oper. Res. 289(3):1127–1141.Crossref, Google Scholar
- (2022) Distributionally robust inventory control when demand is a martingale. Math. Oper. Res. 47(3):2387–2414.Link, Google Scholar
- (2019) A survey of adjustable robust optimization. Eur. J. Oper. Res. 277(3):799–813.Crossref, Google Scholar
- (2004) An adaptive forecasting algorithm and inventory policy for products with short life cycles. Naval Res. Logist. 51(5):633–653.Crossref, Google Scholar
- (2012) Semiparametric quantile regression with high-dimensional covariates. Statistica Sinica 22(4):1379–1401.Google Scholar
- (2022) Joint estimation and robustness optimization. Management Sci. 68(3):1659–1677.Link, Google Scholar

