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.
This research is supported by the Danish Maritime Fund, Grant No. 2016-064.
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- 1.
SF can just as well be defined as the sum of forces aft of the cross-section. The reason is that since the vessel is at hydrostatic equilibrium, the two forces must be equal, but with opposite sign.
- 2.
In future versions of the SCM, this point may be divided in the transversal and vertical direction to estimate TM and metacentric height.
- 3.
These constant weight blocks of tanks are added to the lightship blocks in these experiments.
- 4.
Due to the sparsity of the hydrostatic table, in practice we interpolate the trim and draft from nearby entries.
References
Ambrosino, D., Paolucci, M., Sciomachen, A.: A MIP heuristic for multi poty stowage planning. Transp. Res. Procedia 10, 725–734 (2015)
Avriel, M., Penn, M., Shpirer, N.: Container ship stowage problem: complexity and connection to the coloring of circle graphs. Discrete Appl. Math. 103, 271–279 (2000)
Delgado, A.: Models and algorithms for container vessel stowage optimization. Ph.D. thesis, IT University of Copenhagen (2013)
Economist: The humble hero, May 2013
Economist: Thinking outside the box, April 2018
Interschalt: MACS3 loading computer. http://navis.com
Kang, J., Kim, Y.: Stowage planning in maritime container transportation. J. Oper. Res. Soc. 53(4), 415–426 (2002)
Li, F., Tian, C., Cao, R., Ding, W.: An integer linear programming for container stowage problem. In: Bubak, M., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds.) ICCS 2008. LNCS, vol. 5101, pp. 853–862. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-69384-0_90
Optivation: Mathematical cargomix optimization model for the K-class (2013)
Pacino, D., Delgado, A., Jensen, R.M., Bebbington, T.: Fast generation of near-optimal plans for eco-efficient stowage of large container vessels. In: Böse, J.W., Hu, H., Jahn, C., Shi, X., Stahlbock, R., Voß, S. (eds.) ICCL 2011. LNCS, vol. 6971, pp. 286–301. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-24264-9_22
Pacino, D., Delgado, A., Jensen, R., Bebbington, T.: An accurate model for seaworthy container vessel stowage planning with ballast tanks, pp. 17–32 (2012)
Parreño, F., Pacino, D., Alvarez-Valdes, R.: A GRASP algorithm for the container stowage slot planning problem. Transp. Res. Part E Logist. Transp. Rev. 94, 141–157 (2016)
Tierney, K., Pacino, D., Jensen, R.: On the complexity of container stowage planning problems. Discret. Appl. Math. 169, 225–230 (2014)
UNCTAD: Review of maritime transport 2016. United nations conference on trade and development UNCTAD (2016)
Wilson, I., Roach, P.: Principles of combinatorial optimization applied to container-ship stowage planning. J. Heuristics 5, 403–418 (1999)
Zurheide, S., Fischer, K.: A revenue management slot allocation model for liner shipping networks. Marit. Econ. Logist. 14(3), 334–361 (2012)
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Jensen, R.M., Ajspur, M.L. (2018). The Standard Capacity Model: Towards a Polyhedron Representation of Container Vessel Capacity. In: Cerulli, R., Raiconi, A., Voß, S. (eds) Computational Logistics. ICCL 2018. Lecture Notes in Computer Science(), vol 11184. Springer, Cham. https://doi.org/10.1007/978-3-030-00898-7_11
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DOI: https://doi.org/10.1007/978-3-030-00898-7_11
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