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An improving agent-based engineering strategy for minimizing unproductive situations of cranes in a rail–rail transshipment yard
Normandie University, UNIHAVRE, 76600 Le Havre, France; Cadi Ayyad University of Marrakech, Morocco.ORCID iD: 0000-0003-3439-6982
International University of Rabat, Morocco.
Normandie University, UNIHAVRE, 76600 Le Havre, France; Cadi Ayyad University of Marrakech, Morocco.
Normandie University, UNIHAVRE, 76600 Le Havre, France.
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2018 (English)In: Simulation, ISSN 0037-5497, Vol. 94, no 8, p. 681-705Article in journal (Refereed) Published
Abstract [en]

Nowadays, seaports seek to achieve a better massification (massive transportation of containers) share of their hinterland transport by promoting rail and river connections in order to more rapidly evacuate increasing container traffic shipped by sea and to avoid landside congestion. The attractiveness of a seaport to shipping enterprises depends not only on its reliability and nautical qualities but also on its massified hinterland connection capacity. Contrary to what has been observed in Europe, the massification share of Le Havre seaport has stagnated in recent years. To overcome this situation, Le Havre Port Authority is putting into service a multimodal hub terminal linked only with massified modes. In this study, we focus on rail–rail transshipment of this new terminal, specifically on minimizing unproductive situations of cranes to improve crane productivity and to speed up freight train processing. To this end, an improving agent-based engineering strategy called the “crane anti-collision strategy” is proposed and tested using multi-method simulation software (Anylogic). In a numerical study, the simulation results reveal that our developed model is very satisfactory and outperforms other existing simulation models.

Place, publisher, year, edition, pages
SAGE Publications , 2018. Vol. 94, no 8, p. 681-705
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:kth:diva-260265DOI: 10.1177/0037549717733050ISI: 000439330400002Scopus ID: 2-s2.0-85043692245OAI: oai:DiVA.org:kth-260265DiVA, id: diva2:1355031
Note

QC 20191112

Available from: 2019-09-26 Created: 2019-09-26 Last updated: 2024-02-21Bibliographically approved

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Abourraja, Mohamed Nezar

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CiteExportLink to record
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  • apa
  • ieee
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  • de-DE
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