Multi-objective Cross-Docking in Physical Internet Hubs Under Arrival Time Uncertainty

Tarik Chargui (), Fatma Essghaier, Abdelghani Bekrar (), Hamid Allaoui (), Damien Trentesaux () and Gilles Goncalves ()
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Abdelghani Bekrar: LAMIH - Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201 - CNRS - Centre National de la Recherche Scientifique - UPHF - Université Polytechnique Hauts-de-France - INSA Hauts-De-France - INSA Institut National des Sciences Appliquées Hauts-de-France - INSA - Institut National des Sciences Appliquées
Hamid Allaoui: LGI2A - Laboratoire de Génie Informatique et d'Automatique de l'Artois - UA - Université d'Artois
Damien Trentesaux: LAMIH - Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201 - CNRS - Centre National de la Recherche Scientifique - UPHF - Université Polytechnique Hauts-de-France - INSA Hauts-De-France - INSA Institut National des Sciences Appliquées Hauts-de-France - INSA - Institut National des Sciences Appliquées
Gilles Goncalves: LGI2A - Laboratoire de Génie Informatique et d'Automatique de l'Artois - UA - Université d'Artois

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Abstract: Cross-docking terminals or hubs are used by many logistics distribution companies and play a critical role in the performance of the global supply chain. Recent studies on Physical Internet cross-docking hubs (PI-hubs) have shown promising results for optimization problems in different structures such as Road-Road, Rail-Road and Road-Rail PI-hubs. This paper addresses the optimization of trucks' scheduling and PI-containers' grouping in Rail-Road cross-docking PI-hubs. The study is performed considering uncertainty on trucks' arrival time. The problem is formulated as a multi-objective chance constrained mixed integer programming model. The objective is to minimize the number of used wagons, PI-containers distance and the total tardiness of inbound trucks according to a Lexicographic Programming order.

Keywords: Chance constrained programming; Cross-docking; Multi-objective optimization; Rail-road physical internet hub; Truck scheduling; Uncertainty (search for similar items in EconPapers)
Date: 2021-03-03
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Published in Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future, 952, Springer International Publishing, pp.460-472, 2021, Studies in Computational Intelligence, ⟨10.1007/978-3-030-69373-2_33⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03596119

DOI: 10.1007/978-3-030-69373-2_33

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