Metaheuristics for the Two-Dimensional Container Pre-Marshalling Problem

Alan Tus; Andrea Rendl; G. Raidl

Metaheuristics for the Two-Dimensional Container Pre-Marshalling Problem

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

Publikation: Beitrag in Buch oder Tagungsband › Vortrag mit Beitrag in Tagungsband › Begutachtung

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.

Originalsprache	Englisch
Titel	Learning and Intelligent Optimization
Redakteure/-innen	Laetitia Jourdan, Clarisse Dhaenens, Marie-Eléonore Marmion
Seiten	186-201
Seitenumfang	16
Publikationsstatus	Veröffentlicht - 2015
Veranstaltung	Learning and Intelligent Optimization - LION 9 - Dauer: 12 Jan. 2015 → 15 Jan. 2015

Konferenz

Konferenz	Learning and Intelligent Optimization - LION 9
Zeitraum	12/01/15 → 15/01/15

Research Field

Ehemaliges Research Field - Mobility Systems

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@inproceedings{4e953c8449e4429bab4cecd7a89a3c4e,

title = "Metaheuristics for the Two-Dimensional Container Pre-Marshalling Problem",

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.",

author = "Alan Tus and Andrea Rendl and G. Raidl",

year = "2015",

language = "English",

isbn = "978-3-319-19083-9",

pages = "186--201",

editor = "Laetitia Jourdan and Clarisse Dhaenens and Marie-El{\'e}onore Marmion",

booktitle = "Learning and Intelligent Optimization",

note = "Learning and Intelligent Optimization - LION 9 ; Conference date: 12-01-2015 Through 15-01-2015",

}

TY - GEN

T1 - Metaheuristics for the Two-Dimensional Container Pre-Marshalling Problem

AU - Rendl, Andrea

AU - Raidl, G.

A2 - Tus, Alan

A2 - Jourdan, Laetitia

A2 - Dhaenens, Clarisse

A2 - Marmion, Marie-Eléonore

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

M3 - Conference Proceedings with Oral Presentation

SN - 978-3-319-19083-9

SP - 186

EP - 201

BT - Learning and Intelligent Optimization

T2 - Learning and Intelligent Optimization - LION 9

Y2 - 12 January 2015 through 15 January 2015

ER -

Metaheuristics for the Two-Dimensional Container Pre-Marshalling Problem

Abstract

Konferenz

Research Field

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