Rodyti trumpą aprašą

dc.contributor.authorNasirian, Araz
dc.contributor.authorArashpour, Mehrdad
dc.contributor.authorAbbasi, Babak
dc.contributor.authorZavadskas, Edmundas Kazimieras
dc.contributor.authorAkbarnezhad, Ali
dc.date.accessioned2023-09-18T19:43:50Z
dc.date.available2023-09-18T19:43:50Z
dc.date.issued2019
dc.identifier.issn0733-9364
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/142740
dc.description.abstractIn offsite construction, unbalanced distribution of resources can cause heterogeneity in the production environment and result in cost and time overruns. It is of particular importance to efficiently manage resource-constrained production in offsite construction in order to realize its numerous benefits over traditional construction. Although extensive research has been undertaken in the manufacturing domain to address unbalanced resource distribution, such studies in the context of offsite construction are sparse. To bridge this gap, the current study hypothesized that multiskilling and crosstraining of construction resources can provide a cost-effective solution to the problem. The aim of this research was to investigate the extent to which operational benefits can be achieved in offsite construction by using different labor skill set structures to address bottlenecks in production. A hybrid research method that adopts optimization and multicriteria decision-making techniques was used to compare performance measures associated with different labor skill sets. To this end, multiskilling policies were ranked and situations under which ranking results can be changed were discussed. The findings of this study reveal the performance and sensitivity of different multiskilling strategies pertaining to different criteria. This study aids industry practitioners in workforce planning and managing offsite construction. It also contributes to the body of knowledge by quantifying how performance measures and labor skill sets interact with each other.eng
dc.formatPDF
dc.format.extentp. 1-10
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyINSPEC
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.source.urihttps://doi.org/10.1061/(ASCE)CO.1943-7862.0001677
dc.source.urihttps://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CO.1943-7862.0001677
dc.titleSkill set configuration in prefabricated construction: hybrid optimization and multicriteria decision-making approach
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.references41
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionRMIT University, Melbourne
dc.contributor.institutionMonash University, Melbourne
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.institutionThe University of Sydney
dc.contributor.facultyStatybos fakultetas / Faculty of Civil Engineering
dc.subject.researchfieldT 002 - Statybos inžinerija / Construction and engineering
dc.subject.researchfieldS 003 - Vadyba / Management
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics 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.enmultiskilling
dc.subject.enskill set
dc.subject.enoffsite
dc.subject.enconstruction
dc.subject.enbottleneck
dc.subject.enmulticriteria decision making (MCDM)
dc.subject.enpreference ranking organization
dc.subject.enMETHod for enrichment evaluations (PROMETHEE)
dc.subject.enoptimization
dcterms.sourcetitleJournal of construction engineering and management
dc.description.issueiss. 9
dc.description.volumevol. 145
dc.publisher.nameAmerican Society of Civil Engineers
dc.publisher.cityReston
dc.identifier.doi2-s2.0-85068610724
dc.identifier.doi000475459700003
dc.identifier.doi10.1061/(ASCE)CO.1943-7862.0001677
dc.identifier.elaba40276332


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