A New Ant Colony-Based Methodology for Disaster Relief

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dc.contributor.authorFerrer Caja, José María
dc.contributor.authorOrtuño, M. T.
dc.contributor.authorTirado Domínguez, Gregorio
dc.date.accessioned2023-06-17T08:55:55Z
dc.date.available2023-06-17T08:55:55Z
dc.date.issued2020
dc.description.abstractHumanitarian logistics in response to large scale disasters entails decisions that must be taken urgently and under high uncertainty. In addition, the scarcity of available resources sometimes causes the involved organizations to suffer assaults while transporting the humanitarian aid. This paper addresses the last mile distribution problem that arises in such an insecure environment, in which vehicles are often forced to travel together forming convoys for security reasons. We develop an elaborated methodology based on Ant Colony Optimization that is applied to two case studies built from real disasters, namely the 2010 Haiti earthquake and the 2005 Niger famine. There are very few works in the literature dealing with problems in this context, and that is the research gap this paper tries to fill. Furthermore, the consideration of multiple criteria such as cost, time, equity, reliability, security or priority, is also an important contribution to the literature, in addition to the use of specialized ants and effective pheromones that are novel elements of the algorithm which could be exported to other similar problems. Computational results illustrate the efficiency of the new methodology, confirming it could be a good basis for a decision support tool for real operations.
dc.description.departmentDepto. de Estadística e Investigación Operativa
dc.description.facultyFac. de Ciencias Matemáticas
dc.description.refereedTRUE
dc.description.sponsorshipUnión Europea. Horizonte 2020
dc.description.sponsorshipMinisterio de Economía y Competitividad (MINECO)
dc.description.sponsorshipComunidad de Madrid
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/63192
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dc.identifier.doi10.3390/math8040518
dc.identifier.issn2227-7390
dc.identifier.officialurlhttps://doi.org/10.3390/math8040518
dc.identifier.relatedurlhttps://www.mdpi.com/2227-7390/8/4/518
dc.identifier.urihttps://hdl.handle.net/20.500.14352/7546
dc.issue.number4
dc.journal.titleMathematics
dc.language.isoeng
dc.page.initial518
dc.publisherhttps://www.mdpi.com/
dc.relation.projectIDMTM2015-65803-R
dc.relation.projectIDGEO-SAFE (691161)
dc.relation.projectIDCASI–CAM (S2013/ICE-2845)
dc.rightsAtribución 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/es/
dc.subject.cdu51:57
dc.subject.cdu519.87
dc.subject.keywordAnt Colony Optimization
dc.subject.keywordHumanitarian logistics
dc.subject.keywordLast mile distribution
dc.subject.keywordDisaster relief
dc.subject.keywordModelos matemáticos
dc.subject.keywordToma de decisiones
dc.subject.keywordDesastres reales
dc.subject.keywordDistribución del último kilómetro
dc.subject.ucmMatemáticas (Matemáticas)
dc.subject.ucmBiomatemáticas
dc.subject.unesco12 Matemáticas
dc.subject.unesco2404 Biomatemáticas
dc.titleA New Ant Colony-Based Methodology for Disaster Relief
dc.typejournal article
dc.volume.number8
dspace.entity.typePublication
relation.isAuthorOfPublication075d2f7f-c728-4ec0-9a3f-a63ef11e2c74
relation.isAuthorOfPublication9a8e32e5-51d7-41cd-9e5f-781d838bce09
relation.isAuthorOfPublication.latestForDiscovery075d2f7f-c728-4ec0-9a3f-a63ef11e2c74
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