Managing the loading of a car service station using scheduling theory

Effective management of the service station’s production area load is a key factor in improving customer service quality and operational efficiency. The proposed approach to optimizing vehicle distribution among service stations is based on scheduling theory and takes into account station specialization, customer priorities, and waiting time minimization. A dynamic task assignment algorithm, implemented in Python, is developed using a greedy strategy focused on early resource release. A software application with a web interface and a schedule visualization module has been created for practical application. This software product may be of interest to automotive and specialized equipment service companies for managing service station loads. The proposed approach provides a balance between computational efficiency and schedule quality, making it suitable for real-world application in urban service stations.