Lange, Ann-Kathrin Kreuz, Felix Langkau, Sven Jahn, Carlos Clausen, Uwe
Year of Publication:
[Editor:] Jahn, Carlos [Editor:] Kersten, Wolfgang [Editor:] Ringle, Christian M. [Title:] Data Science in Maritime and City Logistics: Data-driven Solutions for Logistics and Sustainability. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 30 [ISBN:] 978-3-7531-2347-9 [Year:] 2020 [Pages:] 211-246
Purpose: Truck appointment systems (TAS) are a widely used method to alleviate peaks in truck arrivals at container terminals in seaports and in the hinterland. One big advantage is the opportunity to reduce operation costs for the terminals and the truck queue length in front of the terminal gate. This study aims to analyze and classify different approaches used in science and industry to determine the quota of allowed trucks per time window. Methodology: A comprehensive systematic literature analysis is applied to identify the different approaches to determine the quota of time windows in science and in industry. Findings: The results of the study show that many approaches have been based on experience and are mostly used to improve individual terminals rather than the port as a whole. Methods used to improve and analyze interrelationships are mainly methods of mathematical optimization and simulation. Originality: The question under consideration was mostly only marginally considered in existing investigations, even though it has a major impact on the success of a TAS. Furthermore, only individual solutions have been examined so far and not the suitability of the approaches compared.
Logistics Industry 4.0 Supply Chain Management Sustainability City Logistics Maritime Logistics Data Science