Kastner, Marvin Kämmerling, Nicolas 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:] 485-519
Purpose: When container terminals are planned or converted, among others the most suitable container handling system needs to be selected and the appropriate terminal layout needs to be designed. These two planning activities are mutually dependent and affect the costs and future operational performance. This leads to the question of how to arrive at a (near-)optimal solution for given criteria. Methodology: A mapping review is conducted to investigate how the container handling system is selected and how the terminal layout is designed. Literature is examined regarding the employed methodology, the performance indicator(s) to optimize, and the way terminal layout and equipment selection have been jointly considered. Findings: Various methods have been used to assess a suitable container handling system and the appropriate layout. Commonly, mathematical optimization is used to arrive at a suggestion and simulation is the tool to evaluate proposed decisions. Aspects such as handling costs, travel distances, or ecological factors are sought to be optimized. Originality: Several literature reviews in the past years investigated approaches to the plethora of scheduling problems at container terminals. Here, the two strategic planning activities equipment selection and layout planning are presented in detail. This publication focuses on how the dependency of the two activities has been han-dled in literature.
Logistics Industry 4.0 Supply Chain Management Sustainability City Logistics Maritime Logistics Data Science