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Metaheuristics for the Two-Dimensional Container Pre-Marshalling Problem

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Learning and Intelligent Optimization (LION 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8994))

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Abstract

We introduce a new problem arising in small and medium-sized container terminals: the Two-Dimensional Pre-Marshalling Problem (2D-PMP). It is an extension of the well-studied Pre-Marshalling Problem (PMP) that is crucial in container storage. The 2D-PMP is particularly challenging due to its complex side constraints that are challenging to express and difficult to consider with standard techniques for the PMP. We present three different heuristic approaches for the 2D-PMP. First, we adapt an existing construction heuristic that was designed for the classical PMP. We then apply this heuristic within two metaheuristics: a Pilot method and a Max-Min Ant System that incorporates a special pheromone model. In our empirical evaluation we observe that the Max-Min Ant System outperforms the other approaches by yielding better solutions in almost all cases.

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Notes

  1. 1.

    http://www.ennshafen.at/en/container_terminal/technical_data.

  2. 2.

    http://www.ads.tuwien.ac.at/w/Research/Problem_Instances.

References

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Acknowledgments

This work is part of the project TRIUMPH, partially funded by the Austrian Federal Ministry for Transport, Innovation and Technology (BMVIT) within the strategic programme I2VSplus under grant 831736. The authors thankfully acknowledge the TRIUMPH project partners Logistikum Steyr (FH OÖ Forschungs&Entwicklungs GmbH), Ennshafen OÖ GmbH, and via donau – Österreichische Wasserstrassen-GmbH. NICTA is funded by the Australian Government through the Department of Communications and the Australian Research Council through the ICT Centre of Excellence Program.

Author information

Authors and Affiliations

  1. Dynamic Transportation Systems, AIT – Austrian Institute of Technology, Mobility Department, Giefinggasse 2, 1180, Vienna, Austria

    Alan Tus

  2. MDCN - Microsoft Development Center Norway, Torggata 2, 0181, Oslo, Norway

    Alan Tus

  3. Optimization Research Group, NICTA and Monash University, School of IT, 878 Dandenong Road, Caulfield East, 3145, Australia

    Andrea Rendl

  4. Institute of Computer Graphics and Algorithms, Vienna University of Technology, Favoritenstraße 9/1861, Vienna, Austria

    Günther R. Raidl

Authors
  1. Alan Tus
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  2. Andrea Rendl
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  3. Günther R. Raidl
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Corresponding author

Correspondence to Alan Tus .

Editor information

Editors and Affiliations

  1. Lille University, Villeneuve d'Ascq, France

    Clarisse Dhaenens

  2. Lille University, Villeneuve d'Ascq, France

    Laetitia Jourdan

  3. Lille University, Villeneuve d'Ascq, France

    Marie-Eléonore Marmion

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Tus, A., Rendl, A., Raidl, G.R. (2015). Metaheuristics for the Two-Dimensional Container Pre-Marshalling Problem. In: Dhaenens, C., Jourdan, L., Marmion, ME. (eds) Learning and Intelligent Optimization. LION 2015. Lecture Notes in Computer Science(), vol 8994. Springer, Cham. https://doi.org/10.1007/978-3-319-19084-6_17

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  • DOI: https://doi.org/10.1007/978-3-319-19084-6_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19083-9

  • Online ISBN: 978-3-319-19084-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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