Modeling Queuing Network at Gröna Lund

Sammanfattning

The visitor experience at an amusement park is crucial for the park’s success. Understanding how guests move through the park is essential when striving to improve design, reduce queue times, and enhance the overall guest experience. This paper applies mathematical modeling to analyze queues at Gröna Lund, a popular amusement park located in central Stockholm. The model, based on principles from queuing theory combined with machine learning, is designed to estimate transition probabilities between attractions. Additionally, the article explores the potential impact of maximizing the use of the park’s attraction capacity to effectively reduce queue formation. Finally, the results are discussed, and recommendations for Gröna Lund are presented.