Design and Implementation of Driver Recommendation Algorithm in Enterprise Transportation

Cargo transportation plays an important role in the manufacturing industry. It is a bridge between the producer and the customer, and the driver is an indispensable part of the goods transportation. Excellent drivers can deliver goods to customers quickly and safely, thus gaining a good reputation for the company and improving its efficiency. In actual production, companies often use manual allocation when arranging the distribution tasks of orders. There will be human subjective factors in it, resulting in unreasonable allocation results. For example, orders from high-quality customers may be allocated to poorer quality customers. The driver will lose customers and cause losses to the company. This paper proposes a driver recommendation algorithm based on machine learning, and proposes an implementation method. By collecting various data generated by the driver when delivering the order, the driver behavior characteristic model is constructed. When a new order is generated, the driver behavior model can be used to match the order with a suitable driver without manual intervention, which improves delivery efficiency and customer satisfaction.