A new algorithm for computing priority vector of pairwise comparisons matrix with fuzzy elements
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19520%2F22%3AA0000285" target="_blank" >RIV/47813059:19520/22:A0000285 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/abs/pii/S0020025522011501" target="_blank" >https://www.sciencedirect.com/science/article/abs/pii/S0020025522011501</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ins.2022.10.030" target="_blank" >10.1016/j.ins.2022.10.030</a>
Alternative languages
Result language
angličtina
Original language name
A new algorithm for computing priority vector of pairwise comparisons matrix with fuzzy elements
Original language description
Applying the Analytic Hierarchy Process (AHP) in a decision making (DM) problem, fuzzy elements are appropriate whenever the decision maker is uncertain about the value of his/her evaluation of the relative importance of the elements in question, i.e., criteria and/or alternatives. The method, often called the fuzzy AHP, is also used when aggregating crisp pairwise comparisons of a group of decision makers in the group DM problem. In this paper, the DM problem is formulated in a general setting using pairwise comparisons matrices with elements from an Abelian linearly ordered group (alo-group). Such an approach enables extensions of traditional multiplicative, additive, or fuzzy approaches. Here, we propose some desirable properties (consistency, coherency, and intensity) of priority vectors, and derive sufficient conditions for the existence of priority vectors with those properties. In general, the most popular methods for deriving the priority vector – the Eigenvector Method and the Geometric Mean Method – do not always provide priority vectors having these desirable properties. Here, we formulate a new solution algorithm for deriving the priority vector based on a specific optimization problem satisfying the desirable properties under appropriate assumptions. Two illustrating examples of the algorithm are presented and discussed.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
<a href="/en/project/GA21-03085S" target="_blank" >GA21-03085S: Supporting Decision Processes with Pairwise Comparisons and Data Mining</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Information Sciences
ISSN
0020-0255
e-ISSN
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Volume of the periodical
615
Issue of the periodical within the volume
November 2022
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
15
Pages from-to
103-117
UT code for WoS article
000890939400006
EID of the result in the Scopus database
2-s2.0-85139857378