dc.contributor.author | Kosareva, Natalja | |
dc.contributor.author | Krylovas, Aleksandras | |
dc.contributor.author | Zavadskas, Edmundas Kazimieras | |
dc.date.accessioned | 2023-09-18T17:09:38Z | |
dc.date.available | 2023-09-18T17:09:38Z | |
dc.date.issued | 2018 | |
dc.identifier.issn | 0424-267X | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/120295 | |
dc.description.abstract | One of the most important stages of solving MCDM problems is normalization of initial decision-making matrix. The impact of 5 widely used normalization methods on the best alternative determination accuracy in the case of ternary estimates decision matrix is analysed in the article. Alternatives ranked by applying SAW method. Monte Carlo procedure was conducted fordata matrices of different dimensions and both optimization directions. Two cases - the more and the less separable alternatives- were analysed.None of the 5 methods were the best or the worst in all cases. Nevertheless, Minmax method inmost cases is significantly better than other. The Log method is the worst in some cases, but it is the best (or one of the best) in other cases.The highest values of the best alternative detection accuracy were accompanied by the lowest standard deviations of experiment results, respectively, the lowest values – by the highest standard deviations. | eng |
dc.format | PDF | |
dc.format.extent | p. 159-175 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.isreferencedby | Scopus | |
dc.relation.isreferencedby | Science Citation Index Expanded (Web of Science) | |
dc.relation.isreferencedby | Social Sciences Citation Index (Web of Science) | |
dc.source.uri | http://www.ecocyb.ase.ro/nr2018_4/11%20-%20Natalja%20KOSAREVA,%20Aleksandras%20KRYLOVAS.pdf | |
dc.title | Statistical analysis of MCDM data normalization methods using Monte Carlo approach. The case of ternary estimates matrix | |
dc.type | Straipsnis Web of Science DB / Article in Web of Science DB | |
dcterms.references | 19 | |
dc.type.pubtype | S1 - Straipsnis Web of Science DB / Web of Science DB article | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.faculty | Fundamentinių mokslų fakultetas / Faculty of Fundamental Sciences | |
dc.contributor.faculty | Statybos fakultetas / Faculty of Civil Engineering | |
dc.contributor.department | Tvariosios statybos institutas / Institute of Sustainable Construction | |
dc.subject.researchfield | N 001 - Matematika / Mathematics | |
dc.subject.researchfield | N 009 - Informatika / Computer science | |
dc.subject.vgtuprioritizedfields | FM0101 - Fizinių, technologinių ir ekonominių procesų matematiniai modeliai / Mathematical models of physical, technological and economic processes | |
dc.subject.ltspecializations | L104 - Nauji gamybos procesai, medžiagos ir technologijos / New production processes, materials and technologies | |
dc.subject.en | normalization methods | |
dc.subject.en | multi-criteria optimization | |
dc.subject.en | Monte Carlo method | |
dc.subject.en | SAW | |
dcterms.sourcetitle | Economic computation and economic cybernetics studies and research | |
dc.description.issue | iss. 4 | |
dc.description.volume | vol. 52 | |
dc.publisher.name | Academy of Economic Studies | |
dc.publisher.city | Bucharest | |
dc.identifier.doi | 000455118900011 | |
dc.identifier.doi | 2-s2.0-85060470334 | |
dc.identifier.doi | 10.24818/18423264/52.4.18.11 | |
dc.identifier.elaba | 33507222 | |