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dc.contributor.authorRani, Pratibha
dc.contributor.authorMishra, Arunodaya Raj
dc.contributor.authorDeveci, Muhammet
dc.contributor.authorAntuchevičienė, Jurgita
dc.date.accessioned2023-09-18T16:17:38Z
dc.date.available2023-09-18T16:17:38Z
dc.date.issued2022
dc.identifier.issn0360-8352
dc.identifier.other(crossref_id)136268844
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/112873
dc.description.abstractAs a generalization of the Fermatean fuzzy set, the theory of interval-valued Fermatean fuzzy set (IVFFS) is a more robust and reliable tool to address the imprecise and incomplete information in the process of multi-criteria decision making (MCDM), thus can be employed on wider range of applications. The aim of this study is to purpose a novel decision-making approach by combining two well-recognized methods, named as the criteria interaction through inter-criteria correlation (CRITIC) and the complex proportional assessment (COPRAS) with IVFFSs. In this line, to compare the interval-valued Fermatean fuzzy numbers (IVFFNs), a new score function is proposed and its feasibility in comparison with existing interval-valued Fermatean fuzzy score and accuracy functions is discussed. To combine the various IVFFNs, some interval-valued Fermatean fuzzy Einstein aggregation operators are introduced. Further, the CRITIC is utilized to derive the objective weights of attributes within IVFFS context. To prioritize the alternatives, the IVFF-COPRAS method is presented on IVFFSs settings. Later, to assess the performance quality of the developed methodology, an illustrative case study is discussed to evaluate and rank the sustainable community-based tourism (CBT) location candidates. Moreover, the comparative study and sensitivity investigation are conducted to prove that the developed framework efficiently handles the problem of sustainable CBT locations evaluation and selection problem under IVFFSs environment. The findings of this study conclude that the developed method is a systematic, more comprehensive, accurate, and structured approach in the assessment of sustainable CBT locations under uncertain environment.eng
dc.formatPDF
dc.format.extentp. 1-20
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScienceDirect
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.relation.isreferencedbyScopus
dc.rightsLaisvai prieinamas internete
dc.source.urihttps://www.sciencedirect.com/science/article/abs/pii/S0360835222002352?via%3Dihub
dc.source.urihttps://talpykla.elaba.lt/elaba-fedora/objects/elaba:127300843/datastreams/MAIN/content
dc.titleNew complex proportional assessment approach using Einstein aggregation operators and improved score function for interval-valued Fermatean fuzzy sets
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.references92
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionRajiv Gandhi National Institute of Youth Development
dc.contributor.institutionGovernment College Raigaon
dc.contributor.institutionImperial College London Turkish Naval Academy
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.facultyStatybos fakultetas / Faculty of Civil Engineering
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics engineering
dc.subject.researchfieldT 002 - Statybos inžinerija / Construction and engineering
dc.subject.researchfieldS 003 - Vadyba / Management
dc.subject.vgtuprioritizedfieldsFM0101 - Fizinių, technologinių ir ekonominių procesų matematiniai modeliai / Mathematical models of physical, technological and economic processes
dc.subject.ltspecializationsL104 - Nauji gamybos procesai, medžiagos ir technologijos / New production processes, materials and technologies
dc.subject.eninterval-valued Fermatean fuzzy sets
dc.subject.enEinstein operators
dc.subject.encommunity based tourism
dc.subject.ensustainable tourism development
dc.subject.enscore function
dc.subject.enMCDM
dc.subject.enCOPRAS
dcterms.sourcetitleComputers & industrial engineering
dc.description.volumevol. 169
dc.publisher.nameElsevier
dc.publisher.cityOxford
dc.identifier.doi136268844
dc.identifier.doi000831313400006
dc.identifier.doi10.1016/j.cie.2022.108165
dc.identifier.elaba127300843


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