Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/30052
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dc.contributor.authorXue, Y-
dc.contributor.authorLi, M-
dc.contributor.authorArabnejad, H-
dc.contributor.authorSuleimenova, D-
dc.contributor.authorJahani, A-
dc.contributor.authorC. Geiger, B-
dc.contributor.authorBoesjes, F-
dc.contributor.authorAnagnostou, A-
dc.contributor.authorJ.E. Taylor, S-
dc.contributor.authorLiu, X-
dc.contributor.authorGroen, D-
dc.date.accessioned2024-11-07T08:53:22Z-
dc.date.available2024-11-07T08:53:22Z-
dc.date.issued2024-09-26-
dc.identifierORCiD: Yani Xue https://orcid.org/0000-0002-7526-9085-
dc.identifierORCiD: Hamid Arabnejad https://orcid.org/0000-0002-0789-1825-
dc.identifierORCiD: Diana Suleimenova https://orcid.org/0000-0003-4474-0943-
dc.identifierORCiD: Alireza Jahani https://orcid.org/0000-0001-9813-352X-
dc.identifierORCiD: Anastasia Anagnostou https://orcid.org/0000-0003-3397-8307-
dc.identifierORCiD: Simon J.E. Taylor https://orcid.org/0000-0001-8252-0189-
dc.identifierORCiD: Derek Groen https://orcid.org/0000-0001-7463-3765-
dc.identifier100017-
dc.identifier.citationXue, Y. et al. (2024) 'Many-Objective Simulation Optimization for Camp Location Problems in Humanitarian Logistics', International Journal of Network Dynamics and Intelligence, 13 (3), 100017, pp. 1 - 14. doi: 10.53941/ijndi.2024.100017.en_US
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/30052-
dc.descriptionData Availability Statement: The Integrated Food Security Phase Classification (IPC) datasets can be downloaded from: https://www.ipcinfo.org/ipc-country-analysis/, the JAXA ALOS Global 30m DSM 2021 dataset can be downloaded from https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_AW3D30_V3_2, the Esri Land Cover 2020 source can be downloaded from https://www.arcgis.com/apps/instant/media/index.html?appid=fc92d38533d440078f17678ebc20e8e2.en_US
dc.description.abstractHumanitarian organizations face a rising number of people fleeing violence or persecution, people who need their protection and support. When this support is given in the right locations, it can be timely, effective and cost-efficient. Successful refugee settlement planning not only considers the support needs of displaced people, but also local environmental conditions and available resources for ensuring survival and health. It is indeed very challenging to find optimal locations for establishing a new refugee camp that satisfy all these objectives. In this paper, we present a novel formulation of the facility location problem with a simulation-based evolutionary many-objective optimization approach to address this problem. We show how this approach, applied to migration simulations, can inform camp selection decisions by demonstrating it for a recent conflict in South Sudan. Our approach may be applicable to diverse humanitarian contexts, and the experimental results have shown it is capable of providing a set of solutions that effectively balance up to five objectives.en_US
dc.description.sponsorshipThis work was supported by the ITFLOWS and HiDALGO projects, which have received funding from the European Union Horizon 2020 research and innovation programme under grant agreement nos 882986 and 824115. It was also supported by UKRI through the ExCALIBUR-funded SEAVEA project initiative (grant agreement number EP/W007762/1).en_US
dc.format.extent1 - 14-
dc.format.mediumElectronic-
dc.language.isoen_USen_US
dc.publisherAustralia Academic Pressen_US
dc.rightsAttribution 4.0 International-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectfacility location problemen_US
dc.subjectmany-objective optimizationen_US
dc.subjectsimulationen_US
dc.subjectevolutionary algorithmsen_US
dc.titleMany-Objective Simulation Optimization for Camp Location Problems in Humanitarian Logisticsen_US
dc.typeArticleen_US
dc.date.dateAccepted2024-08-19-
dc.identifier.doihttps://doi.org/10.53941/ijndi.2024.100017-
dc.relation.isPartOfInternational Journal of Network Dynamics and Intelligence-
pubs.publication-statusPublished online-
dc.identifier.eissn2653-6226-
dc.rights.licensehttps://creativecommons.org/licenses/by/4.0/legalcode.en-
dc.rights.holderThe authors-
Appears in Collections:Dept of Computer Science Research Papers

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