Integrating TOPSIS with interval-valued intuitionistic fuzzy cognitive maps for effective group decision making
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F19%3A39914848" target="_blank" >RIV/00216275:25410/19:39914848 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0020025519301288" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0020025519301288</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ins.2019.02.035" target="_blank" >10.1016/j.ins.2019.02.035</a>
Alternative languages
Result language
angličtina
Original language name
Integrating TOPSIS with interval-valued intuitionistic fuzzy cognitive maps for effective group decision making
Original language description
Many real-life situations require ranking alternative decisions with respect to multiple criteria. The problem becomes more complicated when the knowledge of the considered criteria is vague and unreliable. In order to cope with the vagueness, the values of criteria have to be represented in an approximated way. To overcome the lack of reliability, many experts can be involved in the decision process and thus cooperatively elaborate more credible decisions. However, as it turns out, experts are usually unable to provide plausible information on interactions between vague decision criteria. Since those interactions substantially affect the ranking of alternative decisions, they should be taken into account in the decision process. To effectively cope with that issue, we propose a novel multi-criteria group decision-making method that integrates TOPSIS (technique for order of preference by similarity to ideal solution) with IVIFCMs (interval-valued intuitionistic fuzzy cognitive maps), a tool that is able to model interactions among highly imprecise criteria. We illustrate the application of the proposed IVIFCM-TOPSIS to the supplier selection task. Finally, we present the advantages derived from the use of our method compared to competitive approaches known from the literature. In particular, we show that our method is more consistent than the existing state-of-the-art methods used to solve the addressed decision problem. (C) 2019 Elsevier Inc. All rights reserved.
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
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA16-19590S" target="_blank" >GA16-19590S: Topic and sentiment analysis of multiple textual sources for corporate financial decision-making</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
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
485
Issue of the periodical within the volume
June
Country of publishing house
US - UNITED STATES
Number of pages
19
Pages from-to
394-412
UT code for WoS article
000463121600022
EID of the result in the Scopus database
2-s2.0-85061664222