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dc.contributor.authorZakeri, Shervin
dc.contributor.authorChatterjee, Prasenjit
dc.contributor.authorCheikhrouhou, Naoufel
dc.contributor.authorKonstantas, Dimitri
dc.contributor.authorYang, Yingjie
dc.date.accessioned2023-09-18T16:40:55Z
dc.date.available2023-09-18T16:40:55Z
dc.date.issued2023
dc.identifier.issn0957-4174
dc.identifier.other(SCOPUS_ID)85159629909
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/115933
dc.description.abstractThis paper proposes a new Multiple-criteria decision-making (MCDM) method called MUltiple-TRIangles ScenarioS (MUTRISS) with two scenarios respecting different levels of access to complete information for material selection problems. MUTRISS calculates the areas occupied by alternatives in n-dimensional space, employing analytic geometry and converting each alternative into n-edges forms. The paper applies MUTRISS to three material selection case studies, with Ti-6Al-4V, Material 4, and AISI 4140 Steel- UNS G41400 emerging as the best materials for the three examples with the highest overall scores of 0.036, 4.540 and 0.427 respectively. The results are compared with various MCDM methods through four statistical measures, including relative closeness ratio, robustness analysis, compromise ranking coefficient, and similarity degree. The measures focus on different aspects of MCDM methods in solving problems and their results. The paper concludes that MUTRISS offers a more robust and reliable approach for material selection problems compared to other MCDM methods, with the first scenario of MUTRISS being more reliable than the second scenario. The paper also emphasizes the importance of validating results in material selection problems due to the potential irreversible consequences of selecting the wrong material.eng
dc.formatPDF
dc.format.extentp. 1-17
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbyScienceDirect
dc.source.urihttps://www.sciencedirect.com/science/article/pii/S095741742300965X
dc.titleMUTRISS: A new method for material selection problems using MUltiple-TRIangles scenarios
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.accessRightsThis is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
dcterms.licenseCreative Commons – Attribution – 4.0 International
dcterms.references40
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionUniversity of Geneva University of Applied Sciences Western Switzerland
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.institutionUniversity of Applied Sciences Western Switzerland
dc.contributor.institutionUniversity of Geneva
dc.contributor.institutionDe Montfort University
dc.contributor.facultyStatybos fakultetas / Faculty of Civil Engineering
dc.contributor.departmentTvariosios statybos institutas / Institute of Sustainable Construction
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics engineering
dc.subject.researchfieldT 004 - Aplinkos inžinerija / Environmental engineering
dc.subject.researchfieldT 002 - Statybos inžinerija / Construction and engineering
dc.subject.vgtuprioritizedfieldsIK0303 - Dirbtinio intelekto ir sprendimų priėmimo sistemos / Artificial intelligence and decision support systems
dc.subject.ltspecializationsL104 - Nauji gamybos procesai, medžiagos ir technologijos / New production processes, materials and technologies
dc.subject.enmaterial selection
dc.subject.enanalytic geometry
dc.subject.enmutriss
dc.subject.enrelative closeness ratio
dc.subject.enrobustness analysis
dc.subject.encompromise ranking coefficient
dc.subject.ensimilarity degree
dcterms.sourcetitleExpert systems with applications
dc.description.volumevol. 228
dc.publisher.nameElsevier Ltd
dc.publisher.cityOxford
dc.identifier.doi2-s2.0-85159629909
dc.identifier.doiS095741742300965X
dc.identifier.doi85159629909
dc.identifier.doi1
dc.identifier.doi1-s2.0-S095741742300965X
dc.identifier.doiS0957-4174(23)00965-X
dc.identifier.doi147758432
dc.identifier.doi001009348800001
dc.identifier.doi10.1016/j.eswa.2023.120463
dc.identifier.elaba167563834


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