How Huolala’s “Smart Brain” Uses AI and Optimization to Revolutionize Logistics

On August 13, the China Federation of Logistics and Purchasing hosted the 2020 Global Logistics Technology Conference in Haikou, gathering logistics and supply‑chain leaders worldwide. The event’s theme, “Technology YU See the Future,” focused on cutting‑edge logistics technologies and innovative applications.

Huolala CTO Zhang Hao presented “Operation Optimization in Huolala’s Application,” sharing the company’s “Smart Brain” solution that drives digital and intelligent upgrades in internet logistics.

According to Zhang, the current digital‑intelligent level of internet logistics still has significant room for improvement. Huolala’s tech team’s core mission is to let technology transform logistics, investing continuously in deep digitalization of people, vehicles, cargo and routes to reduce costs and increase efficiency.

Self‑Developed Optimization Algorithms Power Huolala’s Smart Brain

Huolala, an internet logistics platform, integrates social capacity resources through a sharing model to achieve instant intelligent dispatch across multiple vehicle types, offering same‑city and cross‑city freight, enterprise logistics, moving services, less‑than‑truckload, vehicle sales, and post‑sale services.

To meet diverse business scenarios, Huolala built the “Smart Brain” system, delivering an efficient digital‑intelligent solution for internet logistics. Based on AI, big data, and mapping capabilities, it uses a self‑developed optimization algorithm framework to solve core resource allocation problems, and a unified framework to create engines for order splitting, supply‑demand matching, marketing, and pricing, enabling dynamic pricing, intelligent order distribution, capacity dispatch, and user acquisition.

Zhang, a senior data expert, explained that Huolala’s intelligent order‑distribution system processes hundreds of thousands of orders daily, matching them with over 440,000 drivers. The “Smart Brain” analyzes precise user and driver profiles, real‑time driver willingness, and cargo‑capacity conditions to achieve more accurate instant dispatch. Future plans include further algorithm optimization for finer‑grained scenarios.

Digitizing People, Vehicles, Cargo, and Roads to Boost Efficiency and Safety

Internet logistics faces greater challenges than passenger transport due to varying cargo volume, weight, and vehicle types. Achieving higher efficiency in vehicle‑cargo matching requires advancing the digital‑intelligent level of people, vehicles, cargo, and routes.

Huolala now uses IoT devices to collect real‑time vehicle data, combined with machine‑learning algorithms to improve driving and cargo safety and enhance driver service workflow management.

Regarding road digitization, Huolala is strengthening its own mapping capabilities by integrating traditional map technology with deep‑learning methods, leveraging massive freight navigation data to provide positioning, POI search, route planning, navigation, and front‑end services.

Huolala is also experimenting with AR technology for three‑dimensional object recognition and volume measurement, aiming to further improve vehicle‑cargo matching intelligence.

Zhang concluded that logistics’ key barrier is efficiency; Huolala will continue to harness technology to refine fragmented capacity operations, create greater platform value, and contribute to the development of the internet logistics industry.