5 papers
ORPR: An OR-Guided Pretrain-then-Reinforce Learning Model for Inventory Management
Lingjie Zhao, Xue Yu, Yongzhi Qi +6
As the pursuit of synergy between Artificial Intelligence (AI) and Operations Research (OR) gains momentum in handling complex inventory systems, a critical challenge persists: how…
JD.com Improves Fulfillment Efficiency with Data-driven Integrated Assortment Planning and Inventory Allocation
Zuo-Jun Max Shen, Shuo Sun, Yongzhi Qi +5
This paper presents data-driven approaches for integrated assortment planning and inventory allocation that significantly improve fulfillment efficiency at JD\,.com, a leading E-co…
Rethinking Supply Chain Planning: A Generative Paradigm
Jiaheng Yin, Yongzhi Qi, Jianshen Zhang +5
Supply chain planning is the critical process of anticipating future demand and coordinating operational activities across the logistics network. However, within the context of con…
TimeHF: Billion-Scale Time Series Models Guided by Human Feedback
Yongzhi Qi, Hao Hu, Dazhou Lei +6
Time series neural networks perform exceptionally well in real-world applications but encounter challenges such as limited scalability, poor generalization, and suboptimal zero-sho…
Improving Accuracy Without Losing Interpretability: A ML Approach for Time Series Forecasting
Yiqi Sun, Zhengxin Shi, Jianshen Zhang +3
In time series forecasting, decomposition-based algorithms break aggregate data into meaningful components and are therefore appreciated for their particular advantages in interpre…