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Arturas Kaklauskas
Researcher at Vilnius Gediminas Technical University
Publications - 184
Citations - 3943
Arturas Kaklauskas is an academic researcher from Vilnius Gediminas Technical University. The author has contributed to research in topics: Decision support system & Intelligent decision support system. The author has an hindex of 29, co-authored 170 publications receiving 3363 citations.
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Multivariant design and multiple criteria analysis of building refurbishments
TL;DR: In this article, a multivariant design and multiple criteria analysis of a building refurbishment was carried out and much data was processed and evaluated in order to carry out an exhaustive investigation of all solutions that form it.
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Selection of low-e windows in retrofit of public buildings by applying multiple criteria method COPRAS: A Lithuanian case
Arturas Kaklauskas,Edmundas Kazimieras Zavadskas,Saulius Raslanas,Romualdas Ginevičius,Arunas Komka,Pranas Malinauskas +5 more
TL;DR: In this article, the authors presented a practical example (key-case) of selecting a contractor for the replacement of windows in the main building of Vilnius Gediminas Technical University (VGTU) as a part of its retrofit multivariant design.
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Multi-Attribute Decision-Making Model by Applying Grey Numbers
TL;DR: The objective of this research is to demonstrate how simulation can be used to reflect fuzzy inputs, which allows more complete interpretation of model results.
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Multiple criteria assessment of alternatives for built and human environment renovation
Laura Tupenaite,Edmundas Kazimieras Zavadskas,Arturas Kaklauskas,Zenonas Turskis,Mark Seniut +4 more
TL;DR: In this paper, the authors describe the concept of the integrated analysis of built and human environment renovation as a whole as well as presents the multiple criteria assessment of alternatives of the Bulgarian cultural heritage renovation projects.
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Evaluating the life cycle of a building: A multivariant and multiple criteria approach
TL;DR: This approach, in which various criteria can be employed, is intended to support the decision making on a building's life cycle selection and increase the efficiency of the resolution process.