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Given spot and futures prices for vegetable and non‑vegetable oils, refining capacity limits, storage constraints, and a required product hardness range, this model determines the optimal monthly buying, refining, and inventory decisions that maximize profit for a food‑oil manufacturer over a six‑month horizon.
The DataFun Summit 2022 Decision Intelligence online conference on September 24 features leading experts from academia and industry presenting research on supply‑chain optimization, electric‑vehicle service network design, simulation‑based decision frameworks, high‑performance distributed machine‑learning platforms, and advanced optimization solvers.
The TP_AI team from Tsinghua and Peking University details their winning approach to JD’s Global Operations Optimization Challenge, covering regional sales forecasting, two‑level inventory allocation, quantile‑loss evaluation, and practical algorithmic strategies that balance accuracy, constraints, and simplicity.
This article discusses JD.com's Y Business Unit's AI-driven supply chain optimization, focusing on sales prediction algorithms, inventory control, and the challenges of predicting new product sales.