Abstract
Millions of containers are stowed every week with goods worth billions of dollars, but container vessel stowage is an all but neglected combinatorial optimization problem. In this paper, we introduce a model for stowing containers in a vessel bay which is the result of probably the longest collaboration to date with a liner shipping company on automated stowage planning. We then show how to solve this model efficiently in - to our knowledge - the first application of CP to stowage planning using state-of-the-art techniques such as extensive use of global constraints, viewpoints, static and dynamic symmetry breaking, decomposed branching strategies, and early failure detection. Our CP approach outperforms an integer programming and column generation approach in a preliminary study. Since a complete model of this problem includes even more logical constraints, we believe that stowage planning is a new application area for CP with a high impact potential.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Botter, R., Brinati, M.: Stowage container planning: A model for getting an optimal solution. In: Proceedings of the Seventh International Conference on Computer Applications in the Automation of Shipyard Operation and Ship Design (1992)
Giemesh, P., Jellinhaus, A.: Optimization models for the containership stowage problem. In: Proceedings of the International Conference of the German Operations Research Society (2003)
Ambrosino, D., Sciomachen, A., Tanfani, E.: Stowing a conteinership: the master bay plan problem. Transportation Research 38 (2004)
Avriel, M., Penn, M., Shpirer, N., Witteboon, S.: Stowage planning for container ships to reduce the number of shifts. Annals of Operations Research 76(55-71) (1998)
Dubrovsky, O., Penn, M.: A genetic algorithm with a compact solution encoding for the container ship stowage problem. Journal of Heuristics 8(585-599) (2002)
Ambrosino, D., Sciomachen, A., Tanfani, E.: A decomposition heuristics for the container ship stowage problem. Journal of Heuristics 12(3) (2006)
Kang, J., Kim, Y.: Stowage planning in maritime container transportation. Journal of the Operations Research society 53(4) (2002)
Wilson, I., Roach, P.: Principles of combinatorial optimisation applied to container-ship stowage planning. Journal Heuristics 1(5) (1999)
Gumus, M., Kaminsky, P., Tiemroth, E., Ayik, M.: A multi-stage decomposition heuristic for the container stowage problem. In: Proceedings of 2008 MSOM Conference (2008)
Pacino, D., Jensen, R.: A local search extended placement heuristic for stowing under deck bays of container vessels. In: Proceedings of ODYSSEUS 2009 (2009)
Gecode Team: Gecode: Generic constraint development environment (2006), http://www.gecode.org
Rose, H.T., Janstrup, K., Andersen, K.H.: The Container Stowage Problem. Technical report, IT University of Copenhagen (2008)
Smith, B.: Modelling. In: Rossi, F., van Beek, P., Walsh, T. (eds.) Handbook of Constraint Programming. Elsevier, Amsterdam (2006)
Pesant, G.: A regular language membership constraint for finite sequences of variables. In: Wallace, M. (ed.) CP 2004. LNCS, vol. 3258, pp. 482–495. Springer, Heidelberg (2004)
Paul, S.: A constraint for bin packing. In: Wallace, M. (ed.) CP 2004. LNCS, vol. 3258, pp. 648–662. Springer, Heidelberg (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Delgado, A., Jensen, R.M., Schulte, C. (2009). Generating Optimal Stowage Plans for Container Vessel Bays. In: Gent, I.P. (eds) Principles and Practice of Constraint Programming - CP 2009. CP 2009. Lecture Notes in Computer Science, vol 5732. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04244-7_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-04244-7_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04243-0
Online ISBN: 978-3-642-04244-7
eBook Packages: Computer ScienceComputer Science (R0)