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The Standard Capacity Model: Towards a polyhedron representation of container vessel capacity

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Open access

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Host publication Subtitle

9th International conference, ICCL 2018

Original language

English

Pages from-to (Number of pages)

Pages 175-190

Publication milestones

  • Published - 2018

Publication status

Published - 2018

Publisher

Springer, United States, Germany

Book series

  • Book series name: Lecture Notes in Computer Science
    Volume: 11184
    ISSN: 0302-9743
9783030008970

ISBN (Electronic)

9783030008987

Publication IDs

  • Scopus: 85057287178

Host publication title

Computational Logistics

Host 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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