Logistics scheduling based on artificial intelligence: improving logistics efficiency and reducing costs

Author: Zen and the Art of Computer Programming

1 Introduction

1.1 Introduction to the Background of Logistics Scheduling

Logistics scheduling refers to delivering goods to designated locations in an accurate, timely and reasonable manner in the process of warehouse management according to various conditions such as customer needs, system operation status, and inventory. As an important link in the logistics industry, logistics scheduling algorithms play a vital role in optimizing product production and improving economic benefits.

At present, the intelligent logistics dispatching system has gradually become a key link in the operation and management of various enterprises. According to statistics, the scale of the global logistics dispatch market accounts for more than one-third of China's domestic industrial chain and nearly 70% of GDP. Under the background of rapid development of high-tech, cloud computing, big data, Internet, artificial intelligence, etc., the intelligent logistics dispatching system can meet the needs of various complex business scenarios while being intelligent, high-efficiency, and low-cost.

1.2 Composition of dispatching system

A logistics scheduling system usually consists of three main subsystems: supply chain management system (SCM), order management system (OMS) and dispatch management system (DMS). SCM is used to predict and optimize commodity flow, inventory, and transportation routes. OMS is used to manage customer order information, inventory information, and provide real-time feedback on the status of the warehousing system. DMS is used to centrally manage all processes, including order creation, warehousing arrangements, and delivery, and is responsible for the smooth execution of orders.

The logistics scheduling system can be divided into three stages: forecasting, processing and service:

1. Prediction stage: The system will predict the demand, supplier, demand location, time requirement, etc. of the order, and then use data analysis, numerical calculation and other methods to evaluate it, and generate various effective plans to better arrange the delivery of goods.
2. Processing stage: The system will verify the predicted order status, and use the algorithm to schedule, so as to realize the rapid shipment of orders. During this process, the system must consider various factors such as cost, efficiency, environment, and quality to ensure smooth, efficient, and safe logistics.
3. Service phase: