A fuzzy Einstein-based decision support system for public transportation management at times of pandemic

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dc.authoridDursun Delen / 0000-0001-8857-5148en_US
dc.authorscopusidDursun Delen / 55887961100en_US
dc.authorwosidDursun Delen / AGA-9892-2022en_US
dc.contributor.authorDeveci, Muhammet
dc.contributor.authorPamucar, Dragan
dc.contributor.authorGokaşar, Ilgın
dc.contributor.authorDelen, Dursun
dc.contributor.authorMartínez, Luis
dc.date.accessioned2022-08-09T08:03:17Z
dc.date.available2022-08-09T08:03:17Z
dc.date.issued2022en_US
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.description2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)en_US
dc.description.abstractOptimal decision-making has become increasingly more difficult due to their inherent complexity exacerbated by uncertain and rapidly changing environmental conditions in which they are defined. Hence, with the aim of improving the uncertainty management and facilitating the weighting criteria, this paper introduces an improved fuzzy Einstein Combined Compromise Solution (CoCoSo) method- ology. Such a CoCoSo model improves previous CoCoSo proposals by using nonlinear fuzzy weighted Einstein functions for defining weighted sequences. In addition, it proposes a novel algorithm for determining the criteria weights based on the fuzzy logarithmic function, therefore it allows decision- makers a better perception of the relationship between the criteria, as it considers the relationships between adjacent criteria; high consistency of expert comparisons; and enables the definition of weighting coefficients of a larger set of criteria, without the need to cluster (group) the criteria. Nonlinear fuzzy Einstein functions implemented in the fuzzy Einstein CoCoSo methodology enable the processing of complex and uncertain information. Such characteristics contribute to the rational definition of compromise strategies and enable objective reasoning when solving real-world decision problems. The efficiency, effectiveness, and robustness of the proposed fuzzy Einstein CoCoSo model are illustrated by a case study to create a conceptual framework to evaluate and rank the prioritization of public transportation management at the time of the COVID-19 pandemic. The results reveal its good performance in determining the transportation management systems strategy.en_US
dc.identifier.citationDeveci, M., Pamucar, D., Gokasar, I., Delen, D., & Martínez, L. (2022). A fuzzy einstein-based decision support system for public transportation management at times of pandemic. Knowledge-Based Systems, 252 doi:10.1016/j.knosys.2022.109414en_US
dc.identifier.doi10.1016/j.knosys.2022.109414en_US
dc.identifier.issn0950-7051en_US
dc.identifier.scopus2-s2.0-85134799911en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttp://doi.org/10.1016/j.knosys.2022.109414
dc.identifier.urihttps://hdl.handle.net/20.500.12713/3077
dc.identifier.volume252en_US
dc.identifier.wosWOS:000853871500012en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorDelen, Dursun
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofKnowledge-Based Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectPublic Transportation Managementen_US
dc.subjectFuzzy Setsen_US
dc.subjectCoCoSoen_US
dc.subjectEinstein Normsen_US
dc.subjectLogarithmic Additive Functionen_US
dc.titleA fuzzy Einstein-based decision support system for public transportation management at times of pandemicen_US
dc.typeArticleen_US

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