Rodyti trumpą aprašą

dc.contributor.authorHajiagha, Seyed Hossein Razavi
dc.contributor.authorHeidary-Dahooie, Jalil
dc.contributor.authorMeidutė-Kavaliauskienė, Ieva
dc.contributor.authorGovindan, Kannan
dc.date.accessioned2023-09-18T16:17:24Z
dc.date.available2023-09-18T16:17:24Z
dc.date.issued2022
dc.identifier.issn0254-5330
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/112823
dc.description.abstractThis paper presents a new Dynamic Multi-Attribute Decision-Making method based on Markovian property, which can predict the performance of each alternative in the future and at the same time allows modeling interrelationship among different periods. To this aim, the criteria and decision alternatives in different periods are determined at first, and the information of decision matrices over the decision-making horizon is gathered. To increase the robustness of the results, criteria weights are extracted using the Entropy method in each period and alternatives performance is evaluated using different Multi-Attribute Decision-Making methods. To attain the final rank of alternatives in each period, the results of different methods are aggregated by the Correlation coefficient and standard deviation method. Following this, the rank transformation matrices of alternatives during the evaluation horizon are extracted and the stable rank probability of alternatives is calculated based on limiting probability. Eventually, the overall rank of alternatives is determined using a linear assignment-based method. The proposed model has been used in the promotion of the sales staff in a private company to show the model effectiveness in a real-world problem. Results are compared with some well-known methods (five methods, to be exact). Finally, the trustworthiness and acceptability of the method are assessed based on features discussed in the literature.eng
dc.formatPDF
dc.format.extentp. 159-191
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.relation.isreferencedbyScopus
dc.source.urihttps://doi.org/10.1007/s10479-022-04644-0
dc.titleA new dynamic multi-attribute decision making method based on Markov chain and linear assignment
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.references86
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionKhatam University
dc.contributor.institutionUniversity of Tehran
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.institutionShanghai Maritime University Yonsei University University of Southern Denmark
dc.contributor.facultyVerslo vadybos fakultetas / Faculty of Business Management
dc.subject.researchfieldS 003 - Vadyba / Management
dc.subject.studydirectionL02 - Vadyba / Management studies
dc.subject.vgtuprioritizedfieldsEV03 - Dinamiškoji vadyba / Dynamic Management
dc.subject.ltspecializationsL103 - Įtrauki ir kūrybinga visuomenė / Inclusive and creative society
dc.subject.endynamic multi-attribute decision-making (DMADM)
dc.subject.enMarkov chains
dc.subject.enlinear assignment
dc.subject.enpersonnel promotion
dcterms.sourcetitleAnnals of operations research
dc.description.issueiss. 1
dc.description.volumevol. 315
dc.publisher.nameSpringer
dc.publisher.cityDordrecht
dc.identifier.doi2-s2.0-85126514396
dc.identifier.doi85126514396
dc.identifier.doi0
dc.identifier.doi135630801
dc.identifier.doi10.1007/s10479-022-04644-0
dc.identifier.elaba121405354


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