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Dealing with incomplete information in linguistic group decision making by means of Interval Type‐2 Fuzzy Sets

Abstract : Nowadays, in the social network–based decision‐making processes, like the ones involved in e‐commerce and e‐democracy, multiple users with different backgrounds may take part and diverse alternatives might be involved. This diversity enriches the process, but at the same time, increases the uncertainty of opinions. This uncertainty can be considered from two different perspectives: (i) the uncertainty in the meaning of the words given as preferences, that is, motivated by the heterogeneity of the decision makers; and (ii) the uncertainty inherent to any decision‐making process that may lead to an expert not being able to provide all their judgments. The main objective of this study is to address these two types of uncertainty. To do so, the following approaches are proposed: First, to capture, process, and keep the uncertainty in the meaning of the linguistic assumption, the Interval Type‐2 Fuzzy Sets are introduced as a way to model the experts' linguistic judgments. Second, a measure of the coherence of the information provided by each decision maker is proposed. Finally, a consistency‐based completion approach is introduced to deal with the uncertainty presented in the expert judgments. The proposed approach is tested in an e‐democracy decision‐making scenario.
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https://www.hal.inserm.fr/inserm-03026626
Contributor : Christine Dupuis <>
Submitted on : Thursday, November 26, 2020 - 5:29:29 PM
Last modification on : Thursday, November 26, 2020 - 5:30:42 PM

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Raquel Ureña, Gang Kou, Jian Wu, Francisco Chiclana, Enrique Herrera‐viedma. Dealing with incomplete information in linguistic group decision making by means of Interval Type‐2 Fuzzy Sets. International Journal of Intelligent Systems, Wiley, 2019, 34 (6), pp.1261-1280. ⟨10.1002/int.22095⟩. ⟨inserm-03026626⟩

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