Metaheuristics for the Two-Dimensional Container Pre-Marshalling Problem

Alan Tus (Vortragende:r), Andrea Rendl, G. Raidl

    Publikation: Beitrag in Buch oder TagungsbandVortrag mit Beitrag in TagungsbandBegutachtung

    Abstract

    We introduce a new problem arising in small and mediumsized 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.
    OriginalspracheEnglisch
    TitelLearning and Intelligent Optimization
    Redakteure/-innenLaetitia Jourdan, Clarisse Dhaenens, Marie-Eléonore Marmion
    Seiten186-201
    Seitenumfang16
    PublikationsstatusVeröffentlicht - 2015
    VeranstaltungLearning and Intelligent Optimization - LION 9 -
    Dauer: 12 Jan. 201515 Jan. 2015

    Konferenz

    KonferenzLearning and Intelligent Optimization - LION 9
    Zeitraum12/01/1515/01/15

    Research Field

    • Ehemaliges Research Field - Mobility Systems

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