Manage Inventories with Learning on Demands and Buy-up Substitution Probability

References

• Anupindi R, Dada M, Gupta S (1998) Estimation of consumer demand with stock-out based substitution: An application to vending machine products. Marketing Sci. 17(4):406–423.Link, Google Scholar
• Azoury KS (1985) Bayes solution to dynamic inventory models under unknown demand distribution. Management Sci. 31(9):1150–1160.Link, Google Scholar
• Belobaba P (1987) Air Travel Demand and Airline Seat Inventory Management (MIT Press, Cambridge, MA).Google Scholar
• Bensoussan A, Guo P (2015) Technical note—Managing nonperishable inventories with learning about demand arrival rate through stockout times. Oper. Res. 63(3):602–609.Link, Google Scholar
• Bensoussan A, Çakanyildirim M, Sethi SP (2009) Technical note—A note on “The censored newsvendor and the optimal acquisition of information”. Oper. Res. 57(3):791–794.Link, Google Scholar
• Bensoussan A, Çakanyildirim M, Li M, Sethi SP (2016) Managing inventory with cash register information: Sales recorded but not demands. Production Oper. Management 25(1):9–21.Crossref, Google Scholar
• Braden DJ, Freimer M (1991) Informational dynamics of censored observations. Management Sci. 37(11):1390–1404.Link, Google Scholar
• Brumelle SL, McGill JI, Oum TH, Sawaki K, Tretheway MW (1990) Allocation of airline seats between stochastically dependent demands. Transportation Sci. 24(3):183–192.Link, Google Scholar
• Chen L (2010) Bounds and heuristics for optimal Bayesian inventory control with unobserved lost sales. Oper. Res. 58(2):396–413.Link, Google Scholar
• Chen B, Chao X (2019) Parametric demand learning with limited price explorations in a backlog stochastic inventory system. IISE Transactions 51(6):605–613.Crossref, 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 L, Plambeck EL (2008) Dynamic inventory management with learning about the demand distribution and substitution probability. Manufacturing Service Oper. Management 10(2):236–256.Link, Google Scholar
• Chen L, Wu C (2019) Open-loop policies in Bayesian dynamic pricing: Some counter-intuitive observations and insights. Oper. Res. Lett. 47(5):331–338.Crossref, Google Scholar
• Chen L, Mersereau AJ, Wang Z (2017) Optimal merchandise testing with limited inventory. Oper. Res. 65(4):968–991.Link, Google Scholar
• Chu LY, Shanthikumar JG, Shen ZJM (2008) Solving operational statistics via a Bayesian analysis. Oper. Res. Lett. 36(1):110–116.Crossref, Google Scholar
• Cooper WL, Li L (2012) On the use of buy up as a model of customer choice in revenue management. Production Oper. Management 21(5):833–850.Crossref, Google Scholar
• Cooper WL, Homem-de-Mello T, Kleywegt AJ (2006) Models of the spiral-down effect in revenue management. Oper. Res. 54(5):968–987.Link, Google Scholar
• Ding X, Puterman ML, Bisi A (2002) The censored newsvendor and the optimal acquisition of information. Oper. Res. 50(3):517–527.Link, Google Scholar
• Feng Q, Shanthikumar JG (2017) Supply and demand functions in inventory models. Oper. Res. 66(1):77–91.Link, Google Scholar
• Gallego G, Li L, Ratliff R (2009) Choice-based EMSR methods for single-leg revenue management with demand dependencies. J. Revenue Pricing Management 8(2/3):207–240.Crossref, Google Scholar
• Goodfellow I, Bengio Y, Courville A (2016) Deep Learning (MIT Press, Cambridge, MA).Google Scholar
• Harrison JM, Keskin NB, Zeevi A (2012) Bayesian dynamic pricing policies: Learning and earning under a binary prior distribution. Management Sci. 58(3):570–586.Link, Google Scholar
• Hotle SL, Castillo M, Garrow LA, Higgins MJ (2015) The impact of advance purchase deadlines on airline consumers’ search and purchase behaviors. Transp. Res. Part A Policy Pract. 82:1–16.Crossref, Google Scholar
• Hu P, Stephen S, Man Y (2015) Joint inventory and markdown management for perishable goods with strategic consumer behavior. Oper. Res. 64(1):118–134.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
• Ja S, Rao BV, Chandler S (2001) Passenger recapture estimation in airline revenue management. AGIFORS 41st Annual Symposium, AGIFORS, Sydney, Australia.Google Scholar
• Jain A, Rudi N, Wang T (2015) Demand estimation and ordering under censoring: Stock-out timing is (almost) all you need. Oper. Res. 63(1):134–150.Link, Google Scholar
• Kök AG, Fisher ML (2007) Demand estimation and assortment optimization under substitution: Methodology and application. Oper. Res. 55(6):1001–1021.Link, Google Scholar
• Lariviere MA, Porteus EL (1999) Stalking information: Bayesian inventory management with unobserved lost sales. Management Sci. 45(3):346–363.Link, Google Scholar
• Li R, Ryan JK (2011) A Bayesian inventory model using real-time condition monitoring information. Production Oper. Management 20(5):754–771.Crossref, Google Scholar
• Li R, Song JS, Sun S, Zheng X (2022) Fight inventory shrinkage: Simultaneous learning of inventory level and shrinkage rate. Production Oper. Management 31(6):2477–2491.Crossref, Google Scholar
• Littlewood K (1972) Forecasting and control of passenger bookings. Airline Group Internat. Fed. of Oper. Res. Soc. Proc. 12:95–117.Google Scholar
• Liyanage LH, Shanthikumar JG (2005) A practical inventory control policy using operational statistics. Oper. Res. Lett. 33(4):341–348.Crossref, Google Scholar
• Lovejoy WS (1990) Myopic policies for some inventory models with uncertain demand distributions. Management Sci. 36(6):724–738.Link, Google Scholar
• Lu X, Song JS, Zhu K (2005) On “The censored newsvendor and the optimal acquisition of information.” Oper. Res. 53(6):1024–1026.Link, Google Scholar
• McGill JI, van Ryzin G (1999) Revenue management: Research overview and prospects. Transportation Sci. 33(2):233–256.Link, Google Scholar
• Miller BL (1986) Scarf’s state reduction method, flexibility, and a dependent demand inventory model. Oper. Res. 34(1):83–90.Link, Google Scholar
• Pfeifer PE (1989) The airline discount fare allocation problem. Decis. Sci. 20(1):149–157.Crossref, Google Scholar
• Ratliff RM, Rao BV, Narayan CP, Yellepeddi K (2008) A multi-flight recapture heuristic for estimating unconstrained demand from airline bookings. J. Revenue Pricing Management 7(2):153–171.Crossref, Google Scholar
• Scarf H (1959) Bayes solutions of the statistical inventory problem. Ann. Math. Statist. 30(2):490–508.Crossref, Google Scholar
• Scarf H (1960) Some remarks on Bayes solutions to the inventory problem. Naval Res. Logist. 7(4):591–596.Crossref, Google Scholar
• Shaw S (1982) Air Transport: A Marketing Perspective (Pitman Books, London).Google Scholar
• The Alan Turing Institute (2020) Dynamic forecasting with British Airways. Accessed July 2021, https://www.turing.ac.uk/research/impact-stories/dynamic-forecasting-british-airways.Google Scholar
• U.S. Department of Transportation (2019) Fly rights: A consumer guide to air travel. Accessed July 2021, https://www.transportation.gov/airconsumer/fly-rights.Google Scholar
• Ulu C, Honhon D, Alptekinoglu A (2012) Learning consumer tastes through dynamic assortments. Oper. Res. 60(4):833–849.Link, Google Scholar
• van Ryzin G, McGill J (2000) Revenue management without forecasting or optimization: An adaptive algorithm for determining airline seat protection levels. Management Sci. 46(6):760–775.Link, Google Scholar
• Vulcano G, van Ryzin G, Ratliff R (2012) Estimating primary demand for substitutable products from sales transaction data. Oper. Res. 60(2):313–334.Link, 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