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Artificial Intelligence and Decision Making, 2017, Issue 1, Pages 69–83 (Mi iipr238)  

Multi-criteria analysis

Technique of multi-attribute two-level analysis of power plant sites

V. A. Shakirov, P. S. Pankrat’ev

Bratsk State University
Abstract: In this paper, decision-making problem of power plant siting is considered. One of the stages of the problem, which is geographic area selection, is the most complex on such factors as multicriteriality, high degree of data uncertainty, semi-structure. Especially complicating geographic area selection is that further tentative decision demands such as choosing of plant sites and power plant capacity. For the best decision on geographic area selection multi-attribute problem with two levels of alternatives, which are areas and embodiments of the power plant, is formulated. In view of the fact that alternatives analysis conditions on two levels are different, two multi-attribute analysis methods are proposed. Technique of multi-attribute two-level analysis of alternatives using analytic hierarchy process and multi-attribute utility theory is proposed. Technique of analysis of alternatives in conditions of decision maker fuzzy preferences in connection with criteria is proposed. An example of geographic area selection of hydroelectric station is given.
Keywords: multi-attribute two-level analysis, multi-attribute utility theory, analytic hierarchy process, siting of hydroelectric station.
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: V. A. Shakirov, P. S. Pankrat’ev, “Technique of multi-attribute two-level analysis of power plant sites”, Artificial Intelligence and Decision Making, 2017, no. 1, 69–83
Citation in format AMSBIB
\Bibitem{ShaPan17}
\by V.~A.~Shakirov, P.~S.~Pankrat’ev
\paper Technique of multi-attribute two-level analysis of power plant sites
\jour Artificial Intelligence and Decision Making
\yr 2017
\issue 1
\pages 69--83
\mathnet{http://mi.mathnet.ru/iipr238}
\elib{https://elibrary.ru/item.asp?id=28990694}
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  • https://www.mathnet.ru/eng/iipr/y2017/i1/p69
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