Stochastic Predictive Analytics for Stocks in the Newsvendor Problem
This provides a flexible solution for inventory management with limited historical data, though it appears incremental as it builds on existing stochastic approaches.
The authors tackled the Newsvendor problem in inventory management by developing a stochastic model that does not assume a specific demand distribution, and they demonstrated its effectiveness using real-world data from a large electronic marketplace.
This work addresses a key challenge in inventory management by developing a stochastic model that describes the dynamic distribution of inventory stock over time without assuming a specific demand distribution. Our model provides a flexible and applicable solution for situations with limited historical data and short-term predictions, making it well-suited for the Newsvendor problem. We evaluate our model's performance using real-world data from a large electronic marketplace, demonstrating its effectiveness in a practical forecasting scenario.