Research on Food Dynamic Pricing Algorithm Based on Deep Reinforcement Learning
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-9955-2_63
Reference10 articles.
1. Zhou, H., Chen, K., Wang, S.: Two-period pricing and inventory decisions of perishable products with partial lost sales. Eur. J. Oper. Res. 310(2), 611–626 (2023). https://doi.org/10.1016/j.ejor.2023.03.010
2. Lu, R., Hong, S.H., Zhang, X.: A dynamic pricing demand response algorithm for smart grid: reinforcement learning approach. Appl. Energy 2018(220), 220–230 (2018)
3. Zhang, L., Gao, Y., Zhu, H., et al.: Bi-level stochastic real-time pricing model in multi-energy generation system: a reinforcement learning approach. Energy 239, 121926 (2022)
4. Wang, J., Yang, D., Chen, K., et al.: Cruise dynamic pricing based on SARSA algorithm. Marit. Policy Manage. 48(2), 259–282 (2021)
5. Yang, C., Feng, Y., Whinston, A.: Dynamic pricing and information disclosure for fresh produce: an artificial intelligence approach. Prod. Oper. Manage. 31(1), 155–171 (2022)
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