References
- Asheralieva, A. and Niyato, D. (2020) Distributed dynamic resource management and pricing in the IoT systems with blockchain-as-a-service and UAV-enabled mobile edge computing. IEEE Internet of Things Journal, 7(3), 1974–1993.
- Besbes, O. and Zeevi, A. ( 2009) Dynamic pricing without knowing the demand function: Risk bounds and near-optimal algorithms. Operations Research, 57(6), 1407–1420.
- Bish, E.K. and Suwandechochai, R. (2010) Optimal capacity for substitutable products under operational postponement. European Journal of Operational Research, 207(1), 775–783.
- Bondoux, N., Nguyen, A.Q., Fiig, T. and Acuna-Agost, R. ( 2020) Reinforcement learning applied to airline revenue management. Journal of Revenue and Pricing Management, 19, 332–348.
- Ceryan, O., Sahin, O. and Duenyas, I. (2013) Managing demand and supply for multiple products through dynamic pricing and capacity flexibility. Manufacturing and Service Operations Management, 5(1), 86–101.
- Chan, L.M.A., Shen, Z.J.M., Simchi-Levi, D. and Swann, J.L. (2004) Coordination of Pricing and Inventory Decisions: A Survey and Classification, Kluwer Academic Publisher, Boston, MA.
- Chen, M. and Chen, Z-L. (2015) Recent developments in dynamic pricing research: Multiple products, competition, and limited demand information. Products and Operations Management, 24(5), 704–731.
- Chen, M. and Chen, Z-L. (2018) Robust dynamic pricing with two substitutable products. Manufacturing and Service Operations Management, 20(2), 249–268.
- Chen, X. and Simchi-Levi, D. (2012) Pricing and Inventory Management. Oxford University Press, Oxford, UK.
- Cheng, Y. (2009) Real-time demand learning-based Q-learning approach for dynamic pricing in e-retailing setting, in International Symposium on Information Engineering and Electronic Commerce, pp. 594–598, IEEE Conference, Ternopil, Ukraine.
- Chod, J. and Rudi, N. (2005) Resource flexibility with responsive pricing. Operations Research, 53(3), 532–548.
- den Boer, A.V. (2015) Tracking the market: Dynamic pricing and learning in a changing environment. European Journal of Operational Research, 247(3), 914–927.
- Ding, Q., Kouvelis, P. and Milner, J.M. (2007) Dynamic pricing for multiple class deterministic demand fulfillment. IIE Transactions, 39(11), 997–1013.
- Gallego, G. and van Ryzin, G.J. (1997) A multi-product dynamic pricing problem and its applications to network yield management. Operations Research, 45, 24–41.
- Goyal, M. and Netessine, S. (2010) Volume flexibility, product flexibility or both: The role of demand correlation and product substitution. Manufacturing & Service Operations Management, 13(2), 180–193.
- Hanke, J.E. and Wichern, D.W. (2005) Business Forecasting (8th Edition), Pearson, Prentice Hall, NJ.
- Hariharan, S., Liua, T. and Shenm, Z.J.M. (2020) Role of resource flexibility and responsive pricing in mitigating the uncertainties in production systems. European Journal of Operational Research, 284(2), 498–513.
- Kim, B.G., Zhang, Y., Van Der Schaar, M. and Lee, J.W. (2016) Dynamic pricing and energy consumption scheduling with reinforcement learning. IEEE Transactions on SmartGrid, 7, 2187–219.
- Kastius, A. and Schlosser, R. (2021) Dynamic pricing under competition using reinforcement learning. Journal of Revenue and Pricing Management, 21, 50–63.
- Luong, N.C., Wang, P., Dusit, N., Wen, Y. and Han, Z. (2017) Resource management in cloud networking using economic analysis and pricing models: A survey. IEEE Communications Surveys and Tutorials, 19(2), 954–1001.
- Lus, B. and Muriel, A. (2009) Measuring the impact of increased product substitution on pricing and capacity decisions under linear demand models. Production and Operations Management, 18, 95–113.
- Maestre, R., Duque, J., Rubio, A. and Arevalo, J. (2019) Reinforcement learning for fair dynamic pricing. Intelligent Systems and Applications, 120–135.
- Misra, K., Schwartz, E.M. and Abernethy, J. (2019) Dynamic online pricing with incomplete information using multi-bandit experiments. Marketing Science, 38(2), 226–252.
- Rana, R. and Oliveira, F.S. (2015) Dynamic pricing policies for interdependent perishable products or services using reinforcement learning. Expert Systems with Applications, 42(1), 426–436.
- Sharghivand, N., Derakhshan, F. and Siasi, N. (2021). A comprehensive survey on auction mechanism design for cloud/edge resource management and pricing. IEEE Access, 9, 126502–126529.
- Sutton, R. and Barto. A.G. (1998) Reinforcement Learning. The MIT Press, Cambridge, MA.
- Vicil, O. (2021) Inventory rationing on a one-for-one inventory model for two priority customer classes with backorders and lost sales IIE Transactions, 48(10), 955–974.