Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/98609
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dc.contributorDepartment of Applied Mathematicsen_US
dc.creatorWong, EYCen_US
dc.creatorTai, AHen_US
dc.creatorZhou, Een_US
dc.date.accessioned2023-05-10T02:00:39Z-
dc.date.available2023-05-10T02:00:39Z-
dc.identifier.issn1361-9209en_US
dc.identifier.urihttp://hdl.handle.net/10397/98609-
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.rights© 2018 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/.en_US
dc.rightsThe following publication Wong, E. Y., Tai, A. H., & Zhou, E. (2018). Optimising truckload operations in third-party logistics: A carbon footprint perspective in volatile supply chain. Transportation Research Part D: Transport and Environment, 63, 649-661 is available at https://doi.org/10.1016/j.trd.2018.06.009.en_US
dc.subjectCarbon emissionen_US
dc.subjectThird-party logisticsen_US
dc.subjectSustainabilityen_US
dc.subjectTruckload utilisationen_US
dc.titleOptimising truckload operations in third-party logistics : a carbon footprint perspective in volatile supply chainen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage649en_US
dc.identifier.epage661en_US
dc.identifier.volume63en_US
dc.identifier.doi10.1016/j.trd.2018.06.009en_US
dcterms.abstractWith government and customers driving third-party logistics seeking opportunities to improve operation efficiencies and mitigating carbon emissions in the supply chain, third-party logistics firms have been striving to improve their truckload utilization and vehicle routing operations, especially in emission-regulated countries and volatile business environment. Traditional literature has focused on either truckload utilization or vehicle routing operations but seldom integrating carbon emission mitigation in their daily trucking operations. This paper delineates the operation review of three third-party logistics firms in Hong Kong and develops an organisation-based carbon emission measurement metrics for logistics operations. The truckload utilization and routing performance are reviewed, followed by a correlation analysis on the truckload utilization against truck capacity, loading volume, fuel consumption, truck size, travelling distances and number of destinations. An integrated carbon-driven multi-criteria model is developed achieving carbon emission reduction initiatives, time and distance cost penalty, minimizing number of trucks, and improving truck utilization. The integrated mathematical model has been developed into a simulation system which has been tested with evaluated results. The mathematical model is enhanced for the set of cargo items and vehicle fleet with additional factors of arrival time slots and weight. The model assists traffic planners to reduce cargo planning time and optimize the truckload operations. Further development will be focused on adding the dimensions of pallet loading operations and exception rules for customer loading requirements.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationTransportation research. Part D, Transport and environment, Aug. 2018, v. 63, p. 649-661en_US
dcterms.isPartOfTransportation research. Part D, Transport and environmenten_US
dcterms.issued2018-08-
dc.identifier.scopus2-s2.0-85049569902-
dc.identifier.eissn1879-2340en_US
dc.description.validate202305 bcchen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberAMA-0362-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS27622516-
dc.description.oaCategoryGreen (AAM)en_US
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