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dc.contributor.authorLai, Han
dc.contributor.authorLiao, Huchang
dc.contributor.authorWen, Zhi
dc.contributor.authorZavadskas, Edmundas Kazimieras
dc.contributor.authorAl-Barakati, Abdullah
dc.date.accessioned2023-09-18T20:34:27Z
dc.date.available2023-09-18T20:34:27Z
dc.date.issued2020
dc.identifier.issn1392-2785
dc.identifier.other(SCOPUS_ID)85094926784
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/150981
dc.description.abstractWith the rapid growth of available online cloud services and providers for customers, the selection of cloud service providers plays a crucial role in on-demand service selection on a subscription basis. Selecting a suitable cloud service provider requires a careful analysis and a reasonable ranking method. In this study, an improved combined compromise solution (CoCoSo) method is proposed to identify the ranking of cloud service providers. Based on the original CoCoSo method, we analyze the defects of the final aggregation operator in the original CoCoSo method which ignores the equal importance of the three subordinate compromise scores, and employ the operator of “Linear Sum Normalization” to normalize the three subordinate compromise scores so as to make the results reasonable. In addition, we introduce a maximum variance optimization model which can increase the discrimination degree of evaluation results and avoid inconsistent ordering. A numerical example of the trust evaluation of cloud service providers is given to demonstrate the applicability of the proposed method. Furthermore, we perform sensitivity analysis and comparative analysis to justify the accuracy of the decision outcomes derived by the proposed method. Besides, the results of discrimination test also indicate that the proposed method is more effective than the original CoCoSo method in identifying the subtle differences among alternatives.eng
dc.formatPDF
dc.format.extentp. 411-424
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbySocial Sciences Citation Index (Web of Science)
dc.source.urihttps://doi.org/10.5755/j01.ee.31.4.24990
dc.titleAn improved cocoso method with a maximum variance optimization model for cloud service provider selection
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.accessRightsThis article is an Open Access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 (CC BY 4.0) License (http://creativecommons.org/licenses/by/4.0/)
dcterms.licenseCreative Commons – Attribution – 4.0 International
dcterms.references67
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionChongqing Technology and Business University Sichuan University
dc.contributor.institutionSichuan University King Abdulaziz University
dc.contributor.institutionSichuan University
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.institutionKing Abdulaziz University
dc.contributor.facultyStatybos fakultetas / Faculty of Civil Engineering
dc.subject.researchfieldT 002 - Statybos inžinerija / Construction and engineering
dc.subject.studydirectionE05 - Statybos inžinerija / Civil engineering
dc.subject.vgtuprioritizedfieldsSD0404 - Statinių skaitmeninis modeliavimas ir tvarus gyvavimo ciklas / BIM and Sustainable lifecycle of the structures
dc.subject.ltspecializationsL102 - Energetika ir tvari aplinka / Energy and a sustainable environment
dc.subject.enmulti-criteria decision making
dc.subject.encloud service providers selection
dc.subject.encombined compromise solution (CoCoSo)
dc.subject.enmaximum variance
dc.subject.endiscrimination degree
dcterms.sourcetitleInžinerinė ekonomika = Engineering economics
dc.description.issueno. 4
dc.description.volumevol. 31
dc.publisher.nameKauno technologijos universitetas
dc.publisher.cityKaunas
dc.identifier.doi2-s2.0-85094926784
dc.identifier.doi85094926784
dc.identifier.doi1
dc.identifier.doi000583769700003
dc.identifier.doi10.5755/j01.ee.31.4.24990
dc.identifier.elaba74261045


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