Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/228952
Authors: 
Franzkeit, Janna
Schwientek, Anne Kathrina
Jahn, Carlos
Year of Publication: 
2020
Citation: 
[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:] 247-280
Abstract: 
Purpose: The focus of this publication is literature on the Stowage Planning Problem for small container vessels. The problem is important not only for safety reasons con-cerning stability, but also for enhancing efficiency, as restacking of containers is time consuming and therefore expensive. Small vessels are often competing with other modes of transportation. Optimization of loading operations keeps them competi-tive. Methodology: A systematic literature review taking into account journal articles, conference proceedings as well as book chapters has been conducted. The literature is analyzed and categorized to identify directions for further research. Findings: The problem has been researched extensively for large container vessels. The findings are not always applicable for small vessels. Publications focusing on those are still scarce, but the number has increased in recent years. Nevertheless, multiple new directions for further research are identified. Originality: An extensive literature review for the stowage planning problem with a focus on small container vessels has not been published to the authors' knowledge.
Subjects: 
Logistics
Industry 4.0
Supply Chain Management
Sustainability
City Logistics
Maritime Logistics
Data Science
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by-sa/4.0/
Document Type: 
Conference Paper

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