11 papers
SabreAgent: Language Models at Design Time for Lost-Sales Inventory Control
Yang Liu, Yulin Huang, Xue Yu +3
SabreAgent uses a language model at design time to construct two components for lost-sales inventory control: a product-specific seasonal prior and a validation-selected capped bas…
SSPO: Structure-Aware Similarity-Weighted Preference Optimization for Neural Combinatorial Optimization
Yuanyu Li, Jintao Xu, Zijiang Liu +6
Neural combinatorial optimization (NCO) relies on parallel solution sampling for training, yet existing methods fail to fully exploit the rich information latent in a co-sampled so…
Large Language Model for Operations Research Formulation Selection in Multi-Warehouse Inventory Allocation
Jintao Xu, Yingzheng Ma, Jiong Dong +2
Multi-warehouse inventory allocation is typically formulated as a mixed-integer programming (MIP) problem, yet no single formulation consistently matches heterogeneous instance-lev…
SPORD: A Simulation-Propose-then-OR-Dispose Approach for Supply Chain Planning
Jiayin He, Yutong Pan, Sen Yang +5
For years, supply chain planning at e-commerce firms has operated as a collection of isolated projects. Each planning task from static network planning to dynamic warehouse assortm…
Solver-Verified Formulation Generation and Selection for Multi-Warehouse Inventory Allocation Using Large Language Models
Jintao Xu, Yingzheng Ma, Jiong Dong +4
Balance-oriented multi-warehouse inventory allocation is a recurring decision problem in large-scale e-commerce supply chains, in which a fixed replenishment quantity is distribute…
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…
sTransformer: A Modular Approach for Extracting Inter-Sequential and Temporal Information for Time-Series Forecasting
Jiaheng Yin, Zhengxin Shi, Jianshen Zhang +4
In recent years, numerous Transformer-based models have been applied to long-term time-series forecasting (LTSF) tasks. However, recent studies with linear models have questioned t…
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…