Dynamic Inventory and Price Controls Involving Unknown Demand on Discrete Nonperishable Items
Published Online:26 Aug 2020https://doi.org/10.1287/opre.2019.1974
References
- (2009) Dynamic pricing for nonperishable products with demand learning. Oper. Res. 57:1169–1188.Link, Google Scholar
- (2012) Finite-time analysis of the multiarmed bandit problem. Machine Learn. 47:235–256.Crossref, Google Scholar
- (2007) Logarithmic online regret bounds for reinforcement learning. Adv. Neural Inform. Processing Systems 19:49–56.Google Scholar
- (2005) A partially observed Markov decision process for dynamic pricing. Management Sci. 51:1400–1416.Link, Google Scholar
- (2013) On implications of demand censoring in the newsvendor problem. Management Sci. 59:1407–1424.Link, Google Scholar
- (2009) Dynamic pricing without knowing the demand function: Risk bounds and near-optimal algorithms. Oper. Res. 57:1407–1420.Link, Google Scholar
- (2015) On the (surprising) sufficiency of linear models for dynamic pricing with demand learning. Management Sci. 61:723–739.Link, Google Scholar
- (2012) Dynamic pricing under a general parametric choice model. Oper. Res. 60:965–980.Link, Google Scholar
- (1997) Optimal adaptive policies for Markov decision processes. Math. Oper. Res. 22:222–255.Link, Google Scholar
- (2000) Adaptive ordering and pricing for perishable products. Oper. Res. 48:436–443.Link, Google Scholar
- (2019) Coordinating pricing and inventory replenishment with nonparametric demand learning. Oper. Res. 67(4):1035–1052.Link, Google Scholar
- (2016) Nonparametric algorithms for joint pricing and inventory control with lost-sales and censored demand. Working paper, University of Michigan, Ann Arbor.Google Scholar
- (2017) Dynamic pricing and demand learning with limited price experimentation. Oper. Res. 65:1722–1731.Link, Google Scholar
- (2014) Simultaneously learning and optimizing using controlled variance pricing. Management Sci. 60:770–783.Link, Google Scholar
- (2010) Dynamic pricing with a prior on market response. Oper. Res. 58:16–29.Link, Google Scholar
- (1999) Combined pricing and inventory control under uncertainty. Oper. Res. 47:454–475.Link, Google Scholar
- (2018) Online network revenue management using Thompson sampling. Working paper, Massachusetts Institute of Technology, Cambridge.Google Scholar
- (1963) Probability inequalities for sums of bounded random variables. J. Amer. Statist. Assoc. 58:13–30.Crossref, Google Scholar
- (2009) A non-parametric asymptotic analysis of inventory planning with censored demand. Math. Oper. Res. 34:103–123.Link, Google Scholar
- (2011) Adaptive data-driven inventory control with censored demand based on Kaplan-Meier estimator. Oper. Res. 59:929–941.Link, Google Scholar
- (2010) Near-optimal regret bounds for reinforcement learning. J. Machine Learn. Res. 11:1563–1600.Google Scholar
- (1952) Stochastic estimation of the maximum of a regression function. Ann. Math. Statist. 23:462–466.Crossref, Google Scholar
- (1985) Asymptotically efficient adaptive allocation rules. Adv. Appl. Math. 6:4–22.Crossref, Google Scholar
- (1999) Stalking information: Bayesian inventory management with unobserved lost sales. Management Sci. 43:346–363.Link, Google Scholar
- (2015) The data-driven newsvendor problem: New bounds and insights. Oper. Res. 63:1294–1306.Link, Google Scholar
- (2007) Provably near-optimal sampling-based policies for stochastic inventory control models. Math. Oper. Res. 32:821–839.Link, Google Scholar
- (1952) Some aspects of the sequential design of experiments. Bull. Amer. Math. Soc. 58:527–535.Crossref, Google Scholar
- (1951) A stochastic approximation method. Ann. Math. Statist. 22:400–407.Crossref, Google Scholar
- (1959) Bayes solutions of the statistical inventory problem. Ann. Math. Statist. 30:490–508.Crossref, Google Scholar
- (2005) The Logic of Logistics: Theory, Algorithms, and Applications for Logistics and Supply Chain Management. 2nd ed. (Springer, New York).Google Scholar
- (2007) Optimistic linear programming gives logarithmic regret for irreducible MDPs. Adv. Neural Inform. Processing Systems 20:1–8.Google Scholar
- (2014) Close the gaps: A learning-while-doing algorithm for single-product revenue management problems. Oper. Res. 62:318–331.Link, Google Scholar
- (2000) Foundations of Inventory Management (McGraw-Hill, New York).Google Scholar

