AI-based Load Building in Distribution Logistics

The LoadBuilder project aims to optimize the often manual and experience-based process of load formation and truck allocation in logistics using AI. This process is often based on the implicit knowledge of employees, which makes it difficult to train new people. By analyzing historical data, patterns in load formation are to be identified in order to make the previously implicit knowledge visible and usable. Standard and special combinations of loads and transport vehicles are analyzed, visualized and made available in the form of an interactive tool. This facilitates decision-making and supports the integration of new vehicle configurations through specific pattern recognition. The aim is to develop an AI tool that classifies and visualizes similar past load and allocation patterns, thereby providing valuable support for operational planning.