Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/27964
Full metadata record
DC FieldValueLanguage
dc.contributor.authorHEGGEN, Hilde-
dc.contributor.authorMOLENBRUCH, Yves-
dc.contributor.authorCARIS, An-
dc.contributor.authorBRAEKERS, Kris-
dc.date.accessioned2019-04-02T14:09:00Z-
dc.date.available2019-04-02T14:09:00Z-
dc.date.issued2019-
dc.identifier.citationSustainability, 11(6) (Art N° 1634)-
dc.identifier.issn2071-1050-
dc.identifier.urihttp://hdl.handle.net/1942/27964-
dc.description.abstractIntermodal logistics service providers decide on the routing of demand through their service network. Long-haul routing decisions determine the selected departure and arrival terminals for containers and imply corresponding drayage tasks. Traditionally, given these long-haul routes and fixed drayage tasks, drayage operations are planned in a second phase by establishing truck routes to transport containers to and from terminals by truck. In this paper, operational decisions on local drayage routing in large-volume freight regions with multiple terminals on the one hand, and intermodal long-haul routing on the other hand are merged into an integrated intermodal routing problem. Different long-haul routing decisions imply different drayage tasks to be performed and thus impact total trucking costs. The approach aims at reducing the number of road kilometres and increases bundling opportunities by maximising the long-haul capacity utilisation. In this way, it contributes to the modal shift towards intermodal transport and a more sustainable transport system. As a weekly planning horizon is used, a maximum daily active time and a minimum overnight’s rest are included for multi-day drayage routing. A large neighbourhood search heuristic is proposed to solve the integrated intermodal routing problem. This integrated planning approach provides decision support for routing customer orders throughout the intermodal network with the aim of minimising total transport costs and maximising capacity utilisation. Experiments show the added value of the integrated approach, which uses more information to make better-informed decisions and increase the capacity utilisation. The largest savings in trucking costs are obtained for clustered instances with demand characteristics closest to real-life cases. Finally, a real-life case study analyses the impact of tactical service network design decisions on the total operational costs.-
dc.language.isoen-
dc.publisherMDPI-
dc.rightsCopyright 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).-
dc.subject.otherintermodal transport-
dc.subject.otherintegrated routing-
dc.subject.otherintermodal routing-
dc.subject.otherdrayage-
dc.subject.othervehicle routing-
dc.titleIntermodal Container Routing: Integrating Long-Haul Routing and Local Drayage Decisions-
dc.typeJournal Contribution-
dc.identifier.issue6-
dc.identifier.volume11-
local.bibliographicCitation.jcatA1-
local.publisher.placeST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND-
local.type.refereedRefereed-
local.type.specifiedArticle-
local.bibliographicCitation.artnr1634-
local.type.programmeVSC-
dc.source.typeArticle-
dc.identifier.doi10.3390/su11061634-
dc.identifier.isiWOS:000464353500019-
dc.identifier.urlhttps://www.mdpi.com/2071-1050/11/6/1634-
local.provider.typeWeb of Science-
item.fullcitationHEGGEN, Hilde; MOLENBRUCH, Yves; CARIS, An & BRAEKERS, Kris (2019) Intermodal Container Routing: Integrating Long-Haul Routing and Local Drayage Decisions. In: Sustainability, 11(6) (Art N° 1634).-
item.fulltextWith Fulltext-
item.validationecoom 2020-
item.contributorHEGGEN, Hilde-
item.contributorMOLENBRUCH, Yves-
item.contributorCARIS, An-
item.contributorBRAEKERS, Kris-
item.accessRightsOpen Access-
crisitem.journal.eissn2071-1050-
Appears in Collections:Research publications
Files in This Item:
File Description SizeFormat 
sustainability-11-01634-v2.pdfPublished version824.07 kBAdobe PDFView/Open
Show simple item record

SCOPUSTM   
Citations

10
checked on Sep 2, 2020

WEB OF SCIENCETM
Citations

21
checked on May 2, 2024

Page view(s)

160
checked on Sep 6, 2022

Download(s)

146
checked on Sep 6, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.