The Standard Capacity Model: Towards a polyhedron representation of container vessel capacity
- ,
- Mai Lise Ajspur
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOpen access
Publication Information
Output type
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewHost publication Subtitle
9th International conference, ICCL 2018Original language
EnglishPages from-to (Number of pages)
Pages 175-190Publication milestones
- Published - 2018
Publication status
Published - 2018
Publisher
Springer, United States, GermanyBook series
- Book series name: Lecture Notes in Computer Science
Volume: 11184
ISSN: 0302-9743
ISBN (Print)
9783030008970ISBN (Electronic)
9783030008987Publication IDs
- Scopus: 85057287178
Host publication title
Computational LogisticsHost publication editors
- Raffael Cerulli
- Andrea Raiconi
- Stefan Voss
Abstract
Container liner shipping is about matching spare capacity to cargo in need of transport. This can be realized using cargo flow networks, where edges are associated with vessel capacity. It is hard, though, to calculate free capacity of container vessels unless full-blown non-linear stowage optimization models are applied. This may cause such flow network optimization to be intractable. To address this challenge, we introduce the Standard Capacity Model (SCM). SCMs are succinct linear capacity models derived from vessel data that can be integrated in higher order optimization models as mentioned above. In this paper, we introduce the hydrostatic core of the SCM. Our results show that it can predict key parameters like draft, trim, and stress forces accurately and thus can model capacity reductions due to these factors.
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Accepted author manuscript, 2.13 MB
