Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/29347
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dc.contributor.authorGhorbani, M-
dc.contributor.authorSuleimenova, D-
dc.contributor.authorJahani, A-
dc.contributor.authorSaha, A-
dc.contributor.authorXue, Y-
dc.contributor.authorMintram, K-
dc.contributor.authorAnagnostou, A-
dc.contributor.authorTas, A-
dc.contributor.authorLow, W-
dc.contributor.authorTaylor, SJE-
dc.contributor.authorGroen, D-
dc.date.accessioned2024-07-13T19:34:05Z-
dc.date.available2024-07-13T19:34:05Z-
dc.date.issued2024-06-26-
dc.identifierORCiD: Diana Suleimenova https://orcid.org/0000-0003-4474-0943-
dc.identifierORCiD: Alireza Jahani https://orcid.org/0000-0001-9813-352X-
dc.identifierORCiD: Arindam Saha https://orcid.org/0000-0002-1685-4057-
dc.identifierORCiD: Yani Xue https://orcid.org/0000-0002-7526-9085-
dc.identifierORCiD: Kate Mintram https://orcid.org/0000-0001-7180-9200-
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.identifier102371-
dc.identifier.citationGhorbani, M. et al. (2024) 'Flee 3: Flexible agent-based simulation for forced migration', Journal of Computational Science, 81, 102371, pp. 1 - 14. doi: 10.1016/j.jocs.2024.102371.en_US
dc.identifier.issn1877-7503-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/29347-
dc.descriptionData availability: Data will be made available on request.en_US
dc.description.abstractForced migration is a major humanitarian challenge today, with over 100 million people forcibly displaced due to conflicts, violence and other adverse events. The accurate forecasting of migration patterns helps humanitarian organisations to plan an effective humanitarian response in times of crisis, or to estimate the impact of possible conflict and/or intervention scenarios. While existing models are capable of providing such forecasts, they are strongly geared towards forecasting headline arrival numbers and lack the flexibility to explore migration patterns for specific groups, such as children or persons of a specific ethnicity or religion. Within this paper we present Flee 3, an agent-based simulation tool that aims to deliver migration forecasts in a more detailed, flexible and reconfigurable manner. The tool introduces adaptable rules for agent movement and creation, along with a more refined model that flexibly supports factors like food security, ethnicity, religion, gender and/or age. These improvements help broaden the applicability of the code, enabling us to begin building models for internal displacement and non-conflict-driven migration. We validate Flee 3 by applying it to ten historical conflicts in Asia and Africa and comparing our results with UNHCR refugee data. Our validation results show that the code achieves a validation error (averaged relative difference) of less than 0.6 in all cases, i.e. correctly forecasting over 70% of refugee arrivals, which is superior to its predecessor in all but one case. In addition, by exploiting the parallelised simulation code, we are able to simulate migration from a large scale conflict (Ukraine 2022) in less than an hour and with 80% parallel efficiency using 512 cores per run. To showcase the relevance of Flee to practitioners, we present two use cases: one involving an international migration research project and one involving an international NGO. Flee 3 is available at https://github.com/djgroen/flee/releases/tag/v3.1 and documented on https://flee.readthedocs.io.en_US
dc.description.sponsorshipThis work is supported by the ITFLOWS, HiDALGO, and STAMINA projects, which have received funding from the European Union Horizon 2020 research and innovation program under grant agreements no 882986, 824115, and 883441. This work has also been supported by the SEAVEA ExCALIBUR project, which has received funding from EPSRC, United Kingdom under grant agreement EP/W007711/1. Simulation runs have been performed using the ARCHER2 Supercomputer, located at EPCC in Edinburgh (project e723).en_US
dc.format.extent1 - 14-
dc.format.mediumPrint-Electronic-
dc.languageEnglish-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rightsCopyright © 2024 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/).-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectconflict-driven displacementen_US
dc.subjecthuman migrationen_US
dc.subjectemergency response supporten_US
dc.subjectagent-based modellingen_US
dc.subjectparallel computingen_US
dc.titleFlee 3: Flexible agent-based simulation for forced migrationen_US
dc.typeArticleen_US
dc.date.dateAccepted2024-06-21-
dc.identifier.doihttps://doi.org/10.1016/j.jocs.2024.102371-
dc.relation.isPartOfJournal of Computational Science-
pubs.publication-statusPublished-
pubs.volume81-
dc.identifier.eissn1877-7511-
dc.rights.licensehttps://creativecommons.org/licenses/by/4.0/legalcode.en-
dc.rights.holderThe Author(s)-
Appears in Collections:Dept of Computer Science Research Papers

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