Digital Twin in JD Retail Supply Chain: Architecture, Practices, and Future Directions

The presentation introduces the concept of digital twin—creating a dynamic, virtual replica of physical entities using computer graphics and AI—to enable real‑time simulation, monitoring, analysis, and control of JD Retail's extensive supply‑chain network, which spans six business types, over 1,400 warehouses, and nationwide coverage.

Four main topics are covered: (1) an overview of JD Retail's supply‑chain structure and its algorithmic services; (2) challenges in planning‑level problems such as delayed issue detection, deep downstream impact, and difficulty in isolating planning effects; (3) the digital‑twin system comprising three core elements—digital models, data‑driven decision triggers, and solution generation—implemented through intelligent diagnosis, intelligent decision, and end‑to‑end simulation capabilities; (4) a roadmap for future exploration.

The digital‑twin architecture is built on three twin elements: a one‑to‑one digital model, data‑driven decision actions, and algorithmic solution generation. These map to JD's intelligent diagnosis, smart decision, and simulation abilities, forming a closed‑loop decision‑making workflow.

Two practical case studies illustrate the framework. The first, "Inventory Sinking," reduces warehouse‑to‑consumer distance by allowing suppliers to stock directly in front‑mile warehouses, cutting delivery cost and improving timeliness; intelligent diagnosis identifies cost drivers (distance, weight, order structure) using Monte‑Carlo tree‑search. The second, "Multi‑Warehouse Layout Optimization," formulates an integer‑programming model for joint network‑and‑inventory decisions, supplemented by simulation‑generated data to overcome missing historical parameters.

Future directions discuss optimal solution selection, best‑configuration discovery across supply‑chain stages, bottleneck identification, and leveraging digital twin for innovation. A Q&A segment addresses concerns about long supply‑chain chains, model accuracy, multi‑party collaboration, and integration of external logistics resources.