Deep reinforcement learning algorithms for dynamic pricing and inventory management of perishable productsTuğçe YAVUZ, Onur Kaya2024-06-19articleApplied Soft Computing44 citationsclosedNo readable copy stored yet — this record is metadata only.Supply Chain and Inventory ManagementConsumer Market Behavior and PricingReinforcement Learning in RoboticsAbstractNo abstract was published for this record.Citations in this libraryStored only when both papers are in the corpus — 44 citations exist upstream.References2003Dynamic Pricing in the Presence of Inventory Considerations: Research Overview, Current Practices, and Future Directions2004Revenue Management Under a General Discrete Choice Model of Consumer Behavior2012Review of inventory systems with deterioration since 20012010Dynamic Assortment Optimization with a Multinomial Logit Choice Model and Capacity Constraint2010Managing Perishable and Aging Inventories: Review and Future Research Directions2021Deep reinforcement learning for inventory control: A roadmap2017Reinforcement learning approaches for specifying ordering policies of perishable inventory systems2022Data-driven optimal dynamic pricing strategy for reducing perishable food waste at retailersCited by2025Dynamic pricing and inventory control of perishable products by a deep reinforcement learning algorithm