This article explains JD.com's order fulfillment process, including the OFC system, delivery promises like 211 and 411, appointment scheduling, order splitting across warehouses, merchants and payment methods, and the amount‑splitting mechanism that allocates discounts and fees per SKU.
The 9th Global Cloud Computing Conference China showcased ZTO Express Cloud Platform's containerization journey, revealing multi‑cluster strategies, custom K8s extensions, edge‑computing plans, and award‑winning cloud innovations that drive logistics digital transformation.
DeWu WMS combines single‑order fruit‑picking and batch‑seeding methods with dynamic FlowPick task assignment, batch grouping algorithms, and optimized picker paths (S‑, U‑, Z‑shaped) to reduce travel distance, improve density, and streamline multi‑item order consolidation for anti‑counterfeit shipping.
Daily Fresh built a custom address database and advanced LBS system—including location correction, trajectory denoising, and stay‑point analysis—to accurately detect and curb fake delivery sign‑offs, achieving over 96% detection accuracy and industry‑leading results.
This article presents a complete logistics management system case study, covering business requirements, technology stack selection, front‑end and back‑end architecture, core modules such as bill management, receipt handling, vehicle dispatch, and includes full Java code snippets for key operations.
The article details Meituan's five‑year journey in instant logistics, describing how distributed, high‑concurrency backend architectures were progressively upgraded to microservices, how AI is integrated for pricing, ETA and dispatch, and the operational techniques used to ensure scalability, fault tolerance, and high availability.
This article analyzes the rapid growth of O2O home‑delivery, examines the challenges of delivery fulfillment, compares third‑party and self‑built rider models, and presents hybrid, batch‑ordering, and AI‑driven optimization strategies to reduce costs and boost efficiency.
The article examines how community group buying transforms fresh‑food e‑commerce by reducing loss rates through pre‑warehouse logistics, pre‑sale ordering, next‑day delivery and self‑pickup, while also discussing the broader implications for supply‑chain innovation and technology adoption.
Lazada transformed its e‑commerce platform for Southeast Asia by fully cloud‑nativeizing core systems, deploying serverless and container technologies, leveraging AI and progressive hybrid apps for low‑end devices, and building robust CDN, promotion, and logistics algorithms that delivered a 99.99% success rate during Double 11.
This article analyzes the concept of stability governance, outlines its five fault‑management sub‑domains, examines the pain points of an electronic waybill service, and presents a comprehensive three‑phase strategy—prevention, perception, reach, mitigation, and post‑mortem—backed by concrete implementation steps in availability, monitoring, and online emergency handling.
JD.com's intelligent supply‑chain team combined AI‑driven forecasting, S&OP planning, real‑time inventory response, smart fulfillment, anti‑arbitrage detection, price governance, and precise C2M delivery to dramatically cut costs, improve inventory turnover, and deliver a seamless 11.11 shopping experience.
Leveraging large-scale courier trajectory data and spatiotemporal analytics, the DTInf framework infers parcel delivery times by detecting stay points, correcting delivery locations, and matching delivery events using a trained MLP model, achieving a mean absolute error of 401 seconds and outperforming baselines by over 30%.
This tutorial shows how to use Python's urllib and json libraries to call the Kuaidi100 API, retrieve real‑time logistics data for various Chinese courier companies, and display the tracking timeline, while explaining how to discover the correct request URL via browser dev tools.
At the 9th China Logistics Technology Summit, ZTO Express’s Le Aihua explained how AI‑driven intelligent routing and big‑data analytics are reshaping logistics networks, boosting efficiency, cutting costs, and positioning logistics as a critical infrastructure in the post‑pandemic era.
At the 2020 Global Logistics Technology Conference in Haikou, Huolala CTO Zhang Hao detailed the company’s self‑developed “Smart Brain” system, which leverages AI, big‑data analytics, IoT and custom optimization algorithms to achieve real‑time, intelligent dispatch, dynamic pricing and safer, more efficient logistics operations.
This presentation details ZTO Express’s rapid rise from a modest startup to the world’s largest courier by exploring its technology‑driven business model, crowd‑funded expansion, electronic waybills, smart routing, AI customer service, employee equity schemes, and future digital logistics strategies.
SuNing’s AI R&D Center and Logistics Institute created a digital twin platform that maps physical warehouse systems to virtual models, automatically generates simulation scenarios, optimizes strategies, and feeds results back to improve overall storage operations, achieving over 15% efficiency gains.
Meituan uses AI to solve the massive combinatorial routing problem of its food‑delivery network, optimizing rider paths, aiding merchants, providing voice‑controlled ordering for the visually impaired, and deploying computer‑vision, robotics, autonomous vehicles and drones to streamline logistics while keeping riders focused on short‑distance deliveries.
This article explains how Yanxuan created a fully third‑party warehousing and distribution platform that supports domestic and international e‑commerce scenarios, outlines its core business, data and branding capabilities, tackles key operational challenges, and details the system’s evolution from initial setup to automated operations.
Alibaba’s local life smart logistics team presents a KDD 2020 oral paper detailing a deep‑learning model for order fulfillment cycle time (OFCT) estimation in on‑demand food delivery, describing feature engineering, rider encoding, post‑processing operators, and experimental results that significantly improve prediction accuracy and user experience.
Facing growing order volumes and strict timeliness demands, Cainiao’s tech team overhauled its real‑time data warehouse by redesigning data models, adopting Flink for streaming computation, upgrading data services, and exploring innovative tools, sharing practical lessons and future directions for large‑scale logistics analytics.
Carrefour’s new AI‑driven fast‑pick warehouse system, built by Suning, cuts picking time by half and enables over 95% of more than 1,000 daily orders to be delivered within an hour, illustrating the power of big‑data logistics in modern retail.
This article presents a comprehensive study of robot cluster scheduling in modern sorting centers, introducing idle‑time optimization (ITO) and its path‑finding extension (PITO) to minimize workstation idle periods, describing problem modeling, network‑flow formulations, lifelong TAPF extensions, and experimental results that demonstrate over 10% throughput gains.
The COVID‑19 pandemic dramatically reshaped China's logistics sector, spurring rapid growth in online orders, exposing labor shortages, and prompting widespread adoption of unmanned technologies such as autonomous warehouses, heavy‑duty trucks, drones, delivery robots, and smart lockers to improve efficiency and safety.
The JD Health Medicine Urgent Delivery service leverages LBS‑driven store recommendation, full‑channel transaction integration, and AI‑powered recommendation models to deliver medicines within half an hour across more than 100 cities, showcasing cross‑team technical collaboration and operational innovations.
The paper chronicles Meituan’s three‑stage evolution of delivery‑time estimation—from a hierarchical address tree with local linear regression, through a vector‑retrieval system that boosts recall, to a lightweight end‑to‑end deep‑learning model that meets sub‑5 ms latency while delivering progressively lower error and full coverage.
This article examines how B2B warehouse management software can achieve strong user experience by aligning design with real operational scenarios, detailing JWMS’s workflow‑driven interface, help‑center integration, navigation customization, error‑prevention mechanisms, and consistent interaction principles.
This article explains how an intelligent algorithm identifies the exact start and end points of vehicle loading and unloading actions using specialized acceleration features, improving platform utilization, dispatch accuracy, and overall logistics performance while achieving over 95% detection accuracy.
This article explains the business need, challenges, and detailed backend architecture—including business, technical, and deployment designs—of a high‑concurrency, high‑availability overseas logistics tracking system built with Java, Spring, ActiveMQ, Redis, MySQL, and Docker.
This article explains the Vehicle Routing Problem, its many variants, classic exact and heuristic solution methods, and details how Cainiao’s algorithm team built and continuously upgraded an Adaptive Large Neighborhood Search engine—adding rich operators, parallel architectures, and achieving dozens of world‑record results on benchmark datasets.
This article explains the intelligent swing‑hang scheduling algorithm, an AI‑driven multi‑objective genetic approach that uses IoT data to visualize transport, generate cost‑effective vehicle plans, and iteratively evolve optimal routes, thereby reducing empty mileage and improving logistics efficiency.
This article explains how OpenResty, built on Nginx and Lua, powers JD Logistics' high‑throughput, extensible gateway by leveraging non‑blocking I/O, plugin architecture, multi‑level caching, dynamic load balancing, and custom JSON handling to achieve stable, scalable performance.
Meituan’s AI‑driven “Superbrain” platform combines real‑time big‑data processing, fine‑grained location perception, high‑precision ETA forecasting, multi‑rider dispatch and dynamic pricing to cut instant food‑delivery times from about an hour to roughly thirty minutes while boosting efficiency, cost savings and user experience.
The article details how JD Logistics’ extensive warehouse, routing, distribution, and fulfillment systems—leveraging big data, AI, GIS, IoT, and distributed architectures—were engineered and optimized to handle the massive order surge during the 11.11 Global Shopping Festival with high throughput, low latency, and zero incidents.
The article chronicles Meituan’s instant‑logistics system evolution from vertical services to micro‑services, detailing how massive order scale, ultra‑low latency, and fault‑intolerance drove a CAP‑compliant, stateless distributed architecture with AI‑enhanced pricing and matching, robust data‑sync via Databus, automated disaster recovery, and emerging AIOps challenges.
This article explains the fundamentals of Geographic Information Science (GIS), recounts John Snow's historic cholera map as an early GIS example, and details how GIS technology can be leveraged to build a road‑logistics platform that enables real‑time monitoring, dispatch, path planning, and data‑driven decision making for transportation companies.
Marking the 10th anniversary of Double 11, ZTO Technology details how it tackles massive traffic spikes with an automatic sorting management platform, a high‑availability IDC and private cloud, smart voice and face‑recognition services, real‑time data dashboards, and extensive performance testing to ensure stable, fast, and accurate order fulfillment.
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.
Meituan’s AI‑powered Rider Smart Assistant uses voice‑based interaction, real‑time routing, ETA prediction and massive GPS data to solve NP‑hard dispatch problems, cut manual phone calls, shorten order‑acceptance latency and rider wait times, and deliver safer, faster, more efficient same‑city logistics for riders and customers.
This article introduces Ele.me's intelligent scheduling platform, focusing on the pressure‑balancing subsystem and demonstrating how machine‑learning models such as rider capacity estimation and team pressure‑coefficient prediction are designed, trained, and deployed to improve real‑time O2O delivery operations.
The article examines the public dispute between SF Express and Alibaba's Cainiao over data interfaces, explores privacy and security concerns in logistics, proposes a shared platform model, and highlights blockchain as a potential solution for safeguarding user information in the era of big data and IoT.
This article describes a cloud‑based intelligent logistics scheduling platform for food‑delivery services that leverages big‑data analytics, deep‑learning prediction models, and visualisation tools to achieve multi‑objective dynamic optimization, improve dispatch efficiency, and enhance user experience across thousands of cities.
This article explains how Alibaba’s Cainiao leverages big‑data prediction, supply‑chain scheduling, pre‑packing, intelligent routing, electronic waybills and smart sorting to handle billions of parcels during the Double 11 shopping festival, dramatically improving speed, cost and customer experience.
The article chronicles the Qinglong logistics platform from its 2012 MVP launch through successive versions to a smart‑logistics system, detailing architectural evolution, high‑availability, performance, data‑consistency strategies, and user‑experience practices that underpin large‑scale backend development.
The article explores how AI, cloud computing, big data, and advanced logistics power China’s Double 11 shopping festival, turning it into a showcase for cutting‑edge technologies that drive personalization, real‑time analysis, and industry‑wide digital transformation.
The article examines JD.com's strategic focus on user experience—covering pricing, logistics, service, and product quality—and explains how its integrated systems and "no‑no" policy drive operational efficiency and competitive advantage in China's e‑commerce market.
This article examines a MySQL table storing large JSON logistics data, analyzes why its size grows to 130 GB, and presents practical optimizations such as data archiving, JSON field reduction, and schema redesign to keep the table manageable.
This article dissects JD.com’s Qinglong logistics system, detailing its O2O strategy, big‑data‑driven pre‑sorting, AI algorithms, GIS integration, and the evolution from version 1.0 to 3.0, highlighting how these technologies enable ultra‑fast, agile supply‑chain operations.
This article examines JD.com's unique heavy‑asset e‑commerce model, its logistics network that halves product handling, financial services that lower transaction costs, and rural strategies that apply the same efficiency principles to agriculture, illustrating how cost reduction and speed drive its competitive advantage.
