Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/24688
Title: Ship weather routing: A taxonomy and survey
Authors: Zis, Thalis 
Psaraftis, Harilaos N. 
Ding, Li 
Major Field of Science: Engineering and Technology
Field Category: Other Engineering and Technologies
Keywords: Voyage optimization;Maritime transport;Ship weather routing;Speed optimization
Issue Date: 2020
Source: Ocean Engineering, 2020, vol. 2013
Volume: 213
Journal: Ocean Engineering 
Abstract: <p>Ship weather routing has seen considerably increasing attention in recent years in both academia and industry. Problems in this area consider finding the optimal path and sailing speed for a given voyage considering the environmental conditions of wind and waves. The objectives typically consider minimizing operating costs, fuel consumption, or risk of passage. This paper presents a survey of weather routing and voyage optimization research in maritime transportation, explaining the main methodological approaches, and the key disciplines that are dealing with this problem. The main methodologies used to solve the weather routing problem include the isochrone method, dynamic programming, calculus of variations, the use of pathfinding algorithms and heuristics, while in recent years artificial intelligence and machine learning applications have also risen. Most of these methodologies are well established, and have not changed significantly throughout the years, although applications with a combination of these methods have been used. A taxonomy is subsequently presented based on the discipline, application area, methodological approach, and other important parameters. Considering the steep increase in the number of research papers published in recent years, this paper also seeks to propose future research topics in the field. The paper highlights the need to standardize the reporting of savings through weather routing, to facilitate comparisons between methodologies, which could be achieved through the creation of benchmarking instances.</p>
URI: https://hdl.handle.net/20.500.14279/24688
ISSN: 00298018
DOI: 10.1016/j.oceaneng.2020.107697
Rights: © Elsevier
Type: Article
Affiliation : Technical University of Denmark 
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

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