Priority ranking for the best-worst method

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dc.authorwosidWu, Zhibin/AAD-2962-2021
dc.contributor.authorTu, Jiancheng
dc.contributor.authorWu, Zhibin
dc.contributor.authorPedrycz, Witold
dc.date.accessioned2024-05-19T14:39:20Z
dc.date.available2024-05-19T14:39:20Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description.abstractThe best-worst method is a recently developed approach that addresses pairwise comparisons in multi-criteria decision-making problems. It has attracted the interest of many academics and has gained widespread use for its effectiveness in reducing the pairwise comparison times and for its strong performance in maintaining consistency between judgments. However, the existing best-worst method prioritization methods don't consider the indirect judgments and fail to meet several established criteria. This paper first develops two prioritization methods, the approximate eigenvalue method and the logarithmic least squares method, to the best-worst method. Then, the inconsistency thresholds of the proposed prioritization methods are given. Finally, the Monte Carlo simulation method is applied to generate random matrixes to compare the performance of various prioritization methods on the selected criteria and analyze the relationship between different consistency measures. It is found that the logarithmic least squares method is the best prioritization method because of simple calculation, considering indirect judgments and containing minimum violations.en_US
dc.description.sponsorshipNational Natural Science Foundation of China [71971148]; Fundamental Research Funds for the Central Universities [SXYPY202228]en_US
dc.description.sponsorshipAcknowledgement This work was supported by the National Natural Science Foundation of China under Grant 71971148 and by the Fundamental Research Funds for the Central Universities under Grant SXYPY202228.en_US
dc.identifier.doi10.1016/j.ins.2023.03.110
dc.identifier.endpage55en_US
dc.identifier.issn0020-0255
dc.identifier.issn1872-6291
dc.identifier.scopus2-s2.0-85151472156en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage42en_US
dc.identifier.urihttps://doi.org10.1016/j.ins.2023.03.110
dc.identifier.urihttps://hdl.handle.net/20.500.12713/4755
dc.identifier.volume635en_US
dc.identifier.wosWOS:000969502200001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier Science Incen_US
dc.relation.ispartofInformation Sciencesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectBest-Worst Methoden_US
dc.subjectAnalytic Hierarchy Process (Ahp)en_US
dc.subjectPrioritization Methodsen_US
dc.subjectMonte Carlo Simulationen_US
dc.titlePriority ranking for the best-worst methoden_US
dc.typeArticleen_US

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