Multi-expert disaster risk management & response capabilities assessment using interval-valued intuitionistic fuzzy sets

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dc.authoridJaller, Miguel/0000-0003-4053-750X|OTAY, IREM/0000-0001-5895-506X
dc.authorwosidJaller, Miguel/ABD-1007-2020
dc.contributor.authorOtay, Irem
dc.contributor.authorJaller, Miguel
dc.date.accessioned2024-07-18T20:49:19Z
dc.date.available2024-07-18T20:49:19Z
dc.date.issued2020
dc.departmentİstanbul Bilgi Üniversitesien_US
dc.description13th International FLINS Conference on Uncertainity Modeling in Knowledge Engineering and Decision Making (FLINS) -- AUG 21-24, 2018 -- Belfast, NORTH IRELANDen_US
dc.description.abstractThis study focuses on the evaluation of disaster risk management and response (DRMR) processes and capabilities using a multi-expert multi-criteria decision making (MCDM) framework. The proposed framework considers four sets of evaluation and performance criteria: risk knowledge and organization, risk reduction, disaster response management, and disaster response support; and 22 sub-criteria such as regulating risk management, financial management, energy, and public safety. To contend with random perception and utility, lack of information and subjectivity in the human (expert) judgment processes that could be present in expert-based models, the authors propose an interval-valued intuitionistic fuzzy sets (IVIFSs) approach. IVIFSs can handle high levels of uncertainty and define appropriate membership functions. Specifically, the proposed approach incorporates score judgement and possibility degree matrices, and estimates the local and global weights for each assessment criteria. And finally, evaluates the overall performances of the alternatives using intuitionistic fuzzy Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) approach. The authors implemented the framework to the Atlantico State of Colombia, and assessed the disaster risk management and response processes for each for the State's 23 municipalities. The authors discuss sensitivity analysis that illustrates the robustness of the results.en_US
dc.description.sponsorshipFLINSen_US
dc.description.sponsorshipAtlantic Department Government; Colombian General Royalties System; TUBITAK BIDEB 2219-International Postdoctoral Research Fellowship Programmeen_US
dc.description.sponsorshipWe are grateful to the Atlantic Department Government and the Colombian General Royalties System, for having partially financed this work through the LOGPORT Project. This work is also supported by TUBITAK BIDEB 2219-International Postdoctoral Research Fellowship Programme. Thanks are also due to the various stakeholders that provided valuable information for this work. The authors will also like to thank the contributions of Prof Johanna Amaya, and Prof. Luis Fernando Macea for their expert assessments in this study.en_US
dc.identifier.doi10.3233/JIFS-179452
dc.identifier.endpage852en_US
dc.identifier.issn1064-1246
dc.identifier.issn1875-8967
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85078340895en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage835en_US
dc.identifier.urihttps://doi.org/10.3233/JIFS-179452
dc.identifier.urihttps://hdl.handle.net/11411/8167
dc.identifier.volume38en_US
dc.identifier.wosWOS:000506856200079en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIos Pressen_US
dc.relation.ispartofJournal of Intelligent & Fuzzy Systemsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDisaster Managementen_US
dc.subjectRisk Managementen_US
dc.subjectİnterval-Valued İntuitionistic Fuzzy Setsen_US
dc.subjectMcdmen_US
dc.subjectTopsısen_US
dc.subjectMulticriteria Decision-Makingen_US
dc.subjectPerformanceen_US
dc.subjectAhpen_US
dc.titleMulti-expert disaster risk management & response capabilities assessment using interval-valued intuitionistic fuzzy sets
dc.typeConference Object

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