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On qualitative multi-attribute group decision making and its consensus measure: A probability based perspective
Institution:1. Business School, Sichuan University, Chengdu 610064, China;2. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China;1. Graduate Program in Computer Science, PPGI, UFES – Federal University of Espirito Santo, Av. Fernando Ferrari, 514, Espírito Santo, CEP 29075–910 Vitória, ES, Brazil;2. Department of Production Engineering & Graduate Program in Computer Science, PPGI, UFES - Federal University of Espirito Santo, Av. Fernando Ferrari, 514, Espírito Santo, CEP 29075–910 Vitória, ES, Brazil;1. Tecnológico de Monterrey, Mexico;2. Facultad de Contaduría y Administración (Unidad Torreón), Universidad Autonoma de Coahuila, Mexico;3. CEG-IST, Instituto Superior Técnico, Universidade de Lisboa, Portugal;4. Facultad de Informática, Universidad Autonoma de Sinaloa, Josefa Ortiz de Domínguez s/n, Cd Universitaria, Culiacán, Sinaloa 80013, Mexico
Abstract:This paper focuses on qualitative multi-attribute group decision making (MAGDM) with linguistic information in terms of single linguistic terms and/or flexible linguistic expressions. To do so, we propose a new linguistic decision rule based on the concepts of random preference and stochastic dominance, by a probability based interpretation of weight information. The importance weights and the concept of fuzzy majority are incorporated into both the multi-attribute and collective decision rule by the so-called weighted ordered weighted averaging operator with the input parameters expressed as probability distributions over a linguistic term set. Moreover, a probability based method is proposed to measure the consensus degree between individual and collective overall random preferences based on the concept of stochastic dominance, which also takes both the importance weights and the fuzzy majority into account. As such, our proposed approaches are based on the ordinal semantics of linguistic terms and voting statistics. By this, on one hand, the strict constraint of the uniform linguistic term set in linguistic decision making can be released; on the other hand, the difference and variation of individual opinions can be captured. The proposed approaches can deal with qualitative MAGDM with single linguistic terms and flexible linguistic expressions. Two application examples taken from the literature are used to illuminate the proposed techniques by comparisons with existing studies. The results show that our proposed approaches are comparable with existing studies.
Keywords:Linguistic MAGDM  Random preference  Weights  Stochastic dominance  Consensus measure
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