Online Learning for Dual-Index Policies in Dual-Sourcing Systems

References

• 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.Link, Google Scholar
• Allon G, Van Mieghem JA (2010) Global dual sourcing: Tailored base-surge allocation to near-and offshore production. Management Sci. 56(1):110–124.Link, Google Scholar
• Azizzadenesheli K, Lazaric A, Anandkumar A (2016) Reinforcement learning of POMDPs using spectral methods. Feldman V, Rakhlin A, Shamir O, eds. 29th Conf. Learn. Theory, vol. 49 (PMLR, New York), 193–256.Google Scholar
• Besbes O, Gur Y, Zeevi A (2015) Non-stationary stochastic optimization. Oper. Res. 63(5):1227–1244.Link, Google Scholar
• Bulinskaya EV (1964) Some results concerning optimum inventory policies. Theory Probab. Appl. 9(3):389–403.Crossref, Google Scholar
• Chen B, Shi C (2020) Tailored base-surge policies in dual-sourcing inventory systems with demand learning. Technical report, University of Michigan, Ann Arbor.Google Scholar
• Chen B, Chao X, Ahn HS (2019) 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 W, Shi C, Duenyas I (2020) Optimal learning algorithms for stochastic inventory systems with random capacities. Production Oper. Management 29(7):1624–1649.Crossref, Google Scholar
• Chen B, Wang Y, Zhou Y (2023) Optimal policies for dynamic pricing and inventory control with nonparametric censored demands. Management Sci., ePub ahead of print August 31, https://doi.org/10.1287/mnsc.2023.4859.Link, Google Scholar
• Chen B, Simchi-Levi D, Wang Y, Zhou Y (2022) Dynamic pricing and inventory control with fixed ordering cost and incomplete demand information. Management Sci. 68(8):5684–5703.Link, Google Scholar
• Cheung WC, Ma W, Simchi-Levi D, Wang X (2022) Inventory balancing with online learning. Management Sci. 68(3):1776–1807.Link, Google Scholar
• Federgruen A, Liu Z, Lu L (2020) Synthesis and generalization of structural results in inventory management: A generalized convexity property. Math. Oper. Res. 45(2):547–575.Link, Google Scholar
• Federgruen A, Liu Z, Lu L (2022) Dual sourcing: Creating and utilizing flexible capacities with a second supply source. Production Oper. Management 31(7):2789–2805.Crossref, Google Scholar
• Feng Q, Gallego G, Sethi SP, Yan H, Zhang H (2005) Periodic-review inventory model with three consecutive delivery modes and forecast updates. J. Optim. Theory Appl. 124(1):137–155.Crossref, Google Scholar
• Fukuda Y (1964) Optimal policies for the inventory problem with negotiable leadtime. Management Sci. 10(4):690–708.Link, Google Scholar
• Gong XY, Simchi-Levi D (2023) Bandits atop reinforcement learning: Tackling online inventory models with cyclic demands. Management Sci., ePub ahead of print October 26, https://doi.org/10.1287/mnsc.2023.4947.Link, Google Scholar
• Hua Z, Yu Y, Zhang W, Xu X (2015) Structural properties of the optimal policy for dual-sourcing systems with general lead times. IIE Trans. 47(8):841–850.Crossref, Google Scholar
• Huh WT, Janakiraman G, Muckstadt JA, Rusmevichientong P (2009) 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
• Janakiraman G, Seshadri S (2017) Dual sourcing inventory systems: On optimal policies and the value of costless returns. Production Oper. Management 26(2):203–210.Crossref, Google Scholar
• Janakiraman G, Seshadri S, Sheopuri A (2015) Analysis of tailored base-surge policies in dual sourcing inventory systems. Management Sci. 61(7):1547–1561.Link, Google Scholar
• Kleywegt AJ, Shapiro A, Homem-de Mello T (2002) The sample average approximation method for stochastic discrete optimization. SIAM J. Optim. 12(2):479–502.Crossref, Google Scholar
• Levi R, Perakis G, Uichanco J (2015) The data-driven newsvendor problem: New bounds and insights. Oper. Res. 63(6):1294–1306.Link, Google Scholar
• Levi R, Roundy RO, Shmoys DB (2007) Provably near-optimal sampling-based policies for stochastic inventory control models. Math. Oper. Res. 32(4):821–839.Link, Google Scholar
• Li Q, Yu P (2014) Multimodularity and its applications in three stochastic dynamic inventory problems. Manufacturing Service Oper. Management 16(3):455–463.Link, Google Scholar
• Ortner R (2020) Regret bounds for reinforcement learning via Markov chain concentration. J. Artificial Intelligence Res. 67:115–128.Crossref, Google Scholar
• Paulin D (2015) Concentration inequalities for Markov chains by Marton couplings and spectral methods. Electronic J. Probab. 20:1–32.Crossref, Google Scholar
• Sheopuri A, Janakiraman G, Seshadri S (2010) New policies for the stochastic inventory control problem with two supply sources. Oper. Res. 58(3):734–745.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
• Sun J, Van Mieghem JA (2019) Robust dual sourcing inventory management: Optimality of capped dual index policies and smoothing. Manufacturing Service Oper. Management 21(4):912–931.Link, Google Scholar
• Svoboda J, Minner S, Yao M (2021) Typology and literature review on multiple supplier inventory control models. Eur. J. Oper. Res. 293(1):1–23.Crossref, Google Scholar
• Veeraraghavan S, Scheller-Wolf A (2008) Now or later: A simple policy for effective dual sourcing in capacitated systems. Oper. Res. 56(4):850–864.Link, Google Scholar
• Whittemore AS, Saunders SC (1977) Optimal inventory under stochastic demand with two supply options. SIAM J. Appl. Math. 32(2):293–305.Crossref, 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, Van Mieghem JA (2021) Dual-sourcing, dual-mode dynamic stochastic inventory models: A review. Technical report, Chicago University, Chicago.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, 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