UCB-Type Learning Algorithms with Kaplan–Meier Estimator for Lost-Sales Inventory Models with Lead Times

References

• Agrawal R (1995) Sample mean based index policies by o (log n) regret for the multi-armed bandit problem. Adv. Appl. Probab. 27(4):1054–1078.Crossref, Google Scholar
• Agrawal S, Jia R (2022) Learning in structured MDPs with convex cost functions: Improved regret bounds for inventory management. Oper. Res. 70(3):1646–1664.Google Scholar
• Agrawal S, Avadhanula V, Goyal V, Zeevi A (2019) MNL-bandit: A dynamic learning approach to assortment selection. Oper. Res. 67(5):1453–1485.Link, Google Scholar
• Auer P, Cesa-Bianchi N, Fischer P (2002a) Finite-time analysis of the multiarmed bandit problem. Machine Learn. 47(2–3):235–256.Crossref, Google Scholar
• Auer P, Cesa-Bianchi N, Freund Y, Schapire RE (2002b) The nonstochastic multiarmed bandit problem. SIAM J. Comput. 32(1):48–77.Crossref, Google Scholar
• Bu J, Gong X, Yao D (2020) Constant-order policies for lost-sales inventory models with random supply functions: Asymptotics and heuristic. Oper. Res. 68(4):1063–1073.Link, Google Scholar
• Burtini G, Loeppky J, Lawrence R (2015) A survey of online experiment design with the stochastic multi-armed bandit. Preprint, submitted October 2, https://arxiv.org/abs/1510.00757.Google Scholar
• Chen B, Chao X (2020) Dynamic inventory control with stockout substitution and demand learning. Management Sci. 66(11):5108–5127.Link, Google Scholar
• Chen B, Chao X, Ahn H-S (2019a) Coordinating pricing and inventory replenishment with nonparametric demand learning. Oper. Res. 67(4):1035–1052.Abstract, Google Scholar
• Chen B, Chao X, Shi C (2021) Nonparametric learning algorithms for joint pricing and inventory control with lost sales and censored demand. Math. Oper. Res. 46(2):726–756.Link, Google Scholar
• Chen B, Chao X, Wang Y (2020) Technical note-data-based dynamic pricing and inventory control with censored demand and limited price changes. Oper. Res. 68(5):1445–1456.Link, Google Scholar
• Chen X, Stolyar AL, Xin L (2024) Asymptotic optimality of constant-order policies in joint pricing and inventory control models. Math. Oper. Res. 49(1):557–577.Google Scholar
• Chen B, Jiang J, Zhang J, Zhou Z (2022) Learning to order for inventory systems with lost sales and uncertain supplies. Preprint, submitted July 10, https://arxiv.org/abs/2207.04550.Google Scholar
• Cheung WC, Simchi-Levi D, Zhu R (2022) Hedging the drift: Learning to optimize under nonstationarity. Management Sci. 68(3):1696–1713.Link, Google Scholar
• Gao X, Jasin S, Najafi S, Zhang H (2022) Joint learning and optimization for multi-product pricing (and ranking) under a general cascade click model. Management Sci. 68(10):7362–7382.Link, Google Scholar
• Goldberg DA, Katz-Rogozhnikov DA, Lu Y, Sharma M, Squillante MS (2016) Asymptotic optimality of constant-order policies for lost sales inventory models with large lead times. Math. Oper. Res. 41(3):898–913.Link, Google Scholar
• Huh WT, Rusmevichientong P (2009) A nonparametric asymptotic analysis of inventory planning with censored demand. Math. Oper. Res. 34(1):103–123.Link, Google Scholar
• Huh WT, Janakiraman G, Muckstadt JA, Rusmevichientong P (2009a) An adaptive algorithm for finding the optimal base-stock policy in lost sales inventory systems with censored demand. Math. Oper. Res. 34(2):397–416.Link, Google Scholar
• Huh WT, Janakiraman G, Muckstadt JA, Rusmevichientong P (2009b) Asymptotic optimality of order-up-to policies in lost sales inventory systems. Management Sci. 55(3):404–420.Link, Google Scholar
• Huh WT, Levi R, Rusmevichientong P, Orlin JB (2011) Adaptive data-driven inventory control with censored demand based on Kaplan-Meier estimator. Oper. Res. 59(4):929–941.Link, Google Scholar
• Janakiraman G, Roundy RO (2004) Lost-sales problems with stochastic lead times: Convexity results for base-stock policies. Oper. Res. 52(5):795–803.Link, Google Scholar
• Kaplan EL, Meier P (1958) Nonparametric estimation from incomplete observations. J. Amer. Statist. Assoc. 53(282):457–481.Crossref, Google Scholar
• Karlin S, Scarf H (1958) Inventory models of the Arrow-Harris-Marschak type with time lag. Arrow KJ, Karlin S, Scarf H, eds. Studies in the Mathematical Theory of Inventory and Production (Stanford University Press, Stanford, CA), 155–178.Google Scholar
• Lai TL, Robbins H (1985) Asymptotically efficient adaptive allocation rules. Adv. Appl. Math. 6(1):4–22.Crossref, Google Scholar
• Levi R, Janakiraman G, Nagarajan M (2008) A 2-approximation algorithm for stochastic inventory control models with lost sales. Math. Oper. Res. 33(2):351–374.Link, Google Scholar
• Reiman MI (2004) A new and simple policy for the continuous review lost sales inventory model. Unpublished manuscript, Columbia University, New York.Google Scholar
• Robbins H (1952) Some aspects of the sequential design of experiments. Bull. Amer. Math. Soc. (N.S.) 58(5):527–535.Crossref, Google Scholar
• Russo D, Van Roy B (2014) Learning to optimize via posterior sampling. Math. Oper. Res. 39(4):1221–1243.Link, Google Scholar
• Shi C, Chen W, Duenyas I (2016) Nonparametric data-driven algorithms for multiproduct inventory systems with censored demand. Oper. Res. 64(2):362–370.Link, Google Scholar
• Simchi-Levi D, Sun R, Zhang H (2022) Online learning and optimization for revenue management problems with add-on discounts. Management Sci. 68(10):7402–7421.Link, Google Scholar
• Wei L, Jasin S, Xin L (2021) On a deterministic approximation of inventory systems with sequential probabilistic service level constraints. Oper. Res. 69(4):1057–1076.Link, Google Scholar
• Xin L (2021) Understanding the performance of capped base-stock policies in lost-sales inventory models. Oper. Res. 69(1):61–70.Link, Google Scholar
• Xin L (2022) 1.79-approximation algorithms for continuous review single-sourcing lost-sales and dual-sourcing inventory models. Oper. Res. 70(1):111–128.Link, Google Scholar
• Xin L, Goldberg DA (2016) Optimality gap of constant-order policies decays exponentially in the lead time for lost sales models. Oper. Res. 64(6):1556–1565.Link, Google Scholar
• Xin L, Goldberg DA (2018) Asymptotic optimality of tailored base-surge policies in dual-sourcing inventory systems. Management Sci. 64(1):437–452.Link, Google Scholar
• Xin L, He L, Bewli J, Bowman J, Feng H, Qin Z (2017) On the performance of tailored base-surge policies: Theory and application at Walmart.com. Preprint, submitted December 20, https://dx.doi.org/10.2139/ssrn.3090177.Google Scholar
• Yuan H, Luo Q, Shi C (2021) Marrying stochastic gradient descent with bandits: Learning algorithms for inventory systems with fixed costs. Management Sci. 67(10):6089–6115.Link, Google Scholar
• Zhang H, Jasin S (2022) Online learning and optimization of (some) cyclic pricing policies in the presence of patient customers. Manufacturing Service Oper. Management 24(2):1165–1182.Link, Google Scholar
• Zhang H, Chao X, Shi C (2018) Perishable inventory systems: Convexity results for base-stock policies and learning algorithms under censored demand. Oper. Res. 66(5):1276–1286.Link, Google Scholar
• Zhang H, Chao X, Shi C (2020) Closing the gap: A learning algorithm for lost-sales inventory systems with lead times. Management Sci. 66(5):1962–1980.Link, Google Scholar
• Zipkin P (2008) Old and new methods for lost-sales inventory systems. Oper. Res. 56(5):1256–1263.Link, Google Scholar