Dynamic pricing policies for interdependent perishable products or services using reinforcement learning

Expert Systems with Applications

Volumn 42, Issue 1, 2015, Pages 426-436

  Rana, Rupal ^a   Oliveira, Fernando S ^b  

^a LOUGHBOROUGH UNIVERSITY   (United Kingdom)

^b ESSEC BUSINESS SCHOOL   (France)

Author keywords

Dynamic pricing; Reinforcement learning; Revenue management; Service management; Simulation

Indexed keywords

COSTS; STOCHASTIC MODELS; STOCHASTIC SYSTEMS;

DYNAMIC PRICING; DYNAMIC PRICING POLICIES; ELIGIBILITY TRACES; MULTIPLE PRODUCTS; PERISHABLE PRODUCT; REVENUE MANAGEMENT; SERVICE MANAGEMENT; SIMULATION;

REINFORCEMENT LEARNING;

EID: 84906836591     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2014.07.007     Document Type: Article

References (48)

1. Y. Akcay, H.P. Natarajan, and S.H. Xu Joint dynamic pricing of multiple perishable products under consumer choice Management Science 56 8 2010 1345 1361
2. R. Anjos, R.C.H. Cheng, and C.S.M. Currie Maximizing revenue in the airline industry under one-way pricing Journal of the Operational Research Society 55 2004 535 541
3. R. Anjos, R.C.H. Cheng, and C.S.M. Currie Optimal pricing policies for perishable products European Journal of Operational Research 166 2005 246 254 (Pubitemid 40219826)
4. K. Asdemir, V. Jacob, and R. Krishnan Dynamic pricing of multiple home delivery options European Journal of Operational Research 196 2009 246 257
5. O. Besbes, and A. Zeevi Dynamic pricing without knowing the demand function: Risk bounds and near-optimal algorithms Operations Research 57 6 2009 1407 1420
6. G.R. Bitran, and R. Caldentey An overview of pricing models for revenue management Manufacturing & Service Operations Management 53 3 2003 203 229
7. Bitran, G. R., Caldentey, R., Vial, R. (2004). Pricing policies for perishable products with demand substitution. Working paper.
8. W.R. Burkart, R. Klein, and S. Mayer Product line pricing for services with capacity constraints and dynamic substitution European Journal of Operational Research 219 2012 347359
9. S. Chakraborty, T. Ito, and T. Senjyu Smart pricing scheme: A multi-layered scoring rule application Expert Systems with Applications 41 2014 3726 3735
10. C.-C.H. Chan, C.-B. Cheng, and W.-C. Hsien Pricing and promotion strategies of an online shop based on customer segmentation and multiple decision making Expert Systems with Applications 38 2011 14585 14591
11. Y. Cheng Dynamic pricing for multi-product in e-retailing International Conference on Wireless Communication, Networking and Mobile Computing 2007 5476 5479
12. Y. Cheng Dynamic packaging in e-retailing with stochastic demand over finite horizons: A Q-learning approach Expert Systems with Applications 36 2009 472 480
13. W.L. Cooper, T. Homem-de-Mello, and A.J. Kleywegt Models of the spiral-down effect in revenue management Operations Research 54 5 2006 968 987 (Pubitemid 44546532)
14. C.S.M. Currie, R.C.H. Cheng, and H.K. Smith Dynamic pricing of airline tickets with competition Journal of the Operational Research Society 59 2008 1026 1037
15. F.A. Dorca, L.V. Lima, M.A. Fernandes, and C.R. Lopes Comparing strategies for modeling students learning styles through reinforcement learning in adaptive and intelligent educational systems: An experimental analysis Expert Systems with Applications 40 2013 2092 2101
16. J.P.Q. dos Santos, J.D. de Melo, A.D.D. Neto, and D. Aloise Reactive search strategies using reinforcement learning, local search algorithms and variable neighborhood search Expert Systems with Applications 41 2014 4939 4949
17. W. Elmaghraby, and P. Keskinocak Dynamic pricing in the presence of inventory considerations: research overview, current practices, and future directions Management Science 49 10 2003 1287 1309
18. S.B. Eom A survey of operational expert systems in business (1980-1993) Interfaces 26 5 1996 50 70
19. G. Gallego, and G.J. van Ryzin Optimal dynamic pricing of inventories with stochastic demand over finite horizon Management Science 40 1994 999 1020
20. G. Gallego, and G.J. van Ryzin A multi-product dynamic pricing problem and its applications to network yield management Operations Research 45 1997 24 41 (Pubitemid 127684684)
21. A. Gosavi Reinforcement learning: A tutorial survey and recent advances INFORMS Journal on Computing 21 2 2009 178 192
22. A.N. Gosavi, N. Bandla, and T.K. Das A reinforcement learning approach to a single leg airline revenue management problem with multiple fare classes and overbooking IIE Transactions 34 2002 729 752
23. A. Iseri, and B. Karlik An artificial neural networks approach on automotive pricing Expert Systems with Applications 36 2009 2155 2160
24. C. Jiang, and Z. Sheng Case-based reinforcement learning for dynamic inventory control in a multi-agent supply-chain system Expert Systems with Applications 36 3 2009 6520 6526
25. L.P. Kaelbling, M.L. Littman, and A.W. Moore Reinforcement learning: A survey Journal of Artificial Intelligence Research 4 1996 237 285 (Pubitemid 126646155)
26. S.W. Kim, and P.C. Bell Optimal pricing and production decisions in the presence of symmetrical and asymmetrical substitution Omega 39 2011 528 538
27. I.-H. Kwon, C.O. Kim, J. Jun, and J.H. Lee Case-based myopic reinforcement learning for satisfying target service level in supply chain Expert Systems with Applications 35 2008 389 397
28. K.C. Lee, H. Lee, and N. Lee Agent based mobile negotiation for personalized pricing of last minute theatre tickets Expert Systems with Applications 39 2012 9255 9263
29. S.-H. Liao Expert system methodologies and applications - A decade review from 1995 to 2004 Expert Systems with Applications 28 2005 93 103
30. A.E.B. Lim, and J.G. Shanthikumar Relative entropy, exponential utility, and robust dynamic pricing Operations Research 55 2007 198 214 (Pubitemid 46663456)
31. S. Mabu, A. Tjahjadi, and K. Hirasawa Adaptability analysis of genetic network programming with reinforcement learning in dynamically changing environments Expert Systems with Applications 39 16 2012 12349 12357
32. C. Maglaras, and J. Meissner Dynamic pricing strategies for multi-product revenue management problems Manufacturing Service Operations Management 8 2 2006 136 148 (Pubitemid 43666201)
33. J.I. McGill, and G.J. van Ryzin Revenue management: Research overview and prospects Transportation Science 33 2 1999 233 256
34. S. Netessine, S. Savin, and W.Q. Xiao Revenue management through dynamic cross-selling in e-commerce retailing Operations Research 54 5 2006 893 913 (Pubitemid 44546528)
35. F.S. Oliveira A constraint logic programming algorithm for modeling dynamic pricing INFORMS Journal on Computing 20 1 2008 69 77
36. Oliveira, F.S. (2014). Reinforcement learning for business modeling. In: J. Wang (Ed.), Encyclopedia of business analytics and optimization, pp. 2010-2019.
37. J. Palombarini, and E. Martinez SmartGantt - An intelligent system for real time rescheduling based on relational reinforcement learning Expert Systems with Applications 39 2012 10251 10268
38. D. Peteiro-Barral, B. Guijarro-Berdas, B. Prez-Snchez, and O. Fontenla-Romero A comparative study of the scalability of a sensitivity-based learning algorithm for artificial neural networks Expert Systems with Applications 40 10 2013 3900 3905
39. C. Raju, Y. Narahari, and K. Ravikuma Learning dynamic prices in electronic retail markets with customer segmentation Annals of Operations Research 2006 59 75 (Pubitemid 43723993)
40. R. Rana, and F.S. Oliveira Real-time dynamic pricing in a non-stationary environment using model-free reinforcement Omega 2013 10.1016/j.omega.2013.10. 004
41. A. Sen A comparison of fixed and dynamic pricing policies in revenue management Omega 41 2013 586597
42. M. Shin, K. Ryu, and M. Jung Reinforcement learning approach to goal-regulation in a self-evolutionary manufacturing system Expert Systems with Applications 39 2012 8736 8743
43. S.Y. Sohn, T.H. Moon, and K.J. Seok Optimal pricing for mobile manufacturers in competitive market using genetic algorithm Expert Systems with Applications 36 2009 3448 3453
44. R. Sutton, and A.G. Barto Reinforcement learning 1998 The MIT Press Cambridge, Massachusetts
45. K.T. Talluri, and G.J. van Ryzin The theory and practice of revenue management 2005 Springer New York, NY
46. J.N. Tsitsiklis, and B. Van Roy An analysis of temporal-difference learning with function approximation IEEE Transactions 42 5 1997 674 690 (Pubitemid 127760263)
47. D. Zhang, and W.L. Cooper Revenue management for parallel flights with customer choice behavior Operations Research 53 3 2006 415 431 (Pubitemid 41342346)
48. W. Zhao, and Y.S. Zheng Optimal dynamic pricing for perishable assets with nonhomogeneous demand Management Science 46 3 2000 375 388 (Pubitemid 30596825)