Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/91589
DC FieldValueLanguage
dc.contributorDepartment of Industrial and Systems Engineeringen_US
dc.creatorGao, Xen_US
dc.creatorJin, Xen_US
dc.creatorZheng, Pen_US
dc.creatorCui, Cen_US
dc.date.accessioned2021-11-09T06:11:29Z-
dc.date.available2021-11-09T06:11:29Z-
dc.identifier.urihttp://hdl.handle.net/10397/91589-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectMulti-modal transportationen_US
dc.subjectStochastic programmingen_US
dc.subjectCommodity rebalancingen_US
dc.subjectTransportation planningen_US
dc.subjectHumanitarian logisticsen_US
dc.titleMulti-modal transportation planning for multi-commodity rebalancing under uncertainty in humanitarian logisticsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume47en_US
dc.identifier.doi10.1016/j.aei.2020.101223en_US
dcterms.abstractMulti-commodity rebalancing plays a critical role before and during the attack of large-scale disasters. In practice, some relief centers can be out of reach from the ground for vehicles due to the road disruption. Accordingly, alternative transportation systems are essential to maximize fairness and minimize the total transportation time, simultaneously. However, little study has reported on this issue for humanitarian logistics. To address it, a bi-objective stochastic optimization model is proposed to rebalance and transport commodities with the multi-modal transportation system. This work first linearizes the model and then applies an adaptive augmented -constraint method to obtain a number of Pareto-optimal solutions. Furthermore, a case study of an emergency event is carried out, of which the computational results indicate its decision making effectiveness. Lastly, sensitivity analysis on critical parameters is conducted and the trade-off between the objectives is also analyzed to provide valuable managerial insights.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationAdvanced engineering informatics, Jan. 2021, v. 47, 101223en_US
dcterms.isPartOfAdvanced engineering informaticsen_US
dcterms.issued2021-01-
dc.identifier.isiWOS:000630364600012-
dc.identifier.eissn1474-0346en_US
dc.identifier.artn101223en_US
dc.description.validate202111 bchyen_US
dc.description.oaNot applicableen_US
dc.identifier.FolderNumbera1047-n13-
dc.identifier.SubFormID43854-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThis research was supported by the National Natural Science Foundation of China (71861167002, 5183000192) and the National Research Foundation of Korea (NRF) grant funded by the Korea government (NRF-2017R1A2B4004169).en_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2023-01-31en_US
Appears in Collections:Journal/Magazine Article
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