A comparative study of Prophet, Random Forest/Gradient Boosting, and DQN on three supermarket inventory models, whose favorable DRL conclusion is contradicted by its own training curves.
Learning to order for inventory systems with lost sales and uncertain supplies
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2025 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
A Study of Data-driven Methods for Inventory Optimization
A comparative study of Prophet, Random Forest/Gradient Boosting, and DQN on three supermarket inventory models, whose favorable DRL conclusion is contradicted by its own training curves.