Complex & Intelligent Systems · 2019 · 86 citations · 43 references
BusinessDecision SciencesEnvironmental ManagementDecision MakingMulti-criteria Decision MakingSolid Waste ManagementCriteria WeightingDecision SupportFuzzy LogicFuzzy Multi-criteria Decision MakingGroup Decision-makingMulti-criteria Decision AnalysisFuzzy Assessment ModelsFuzzy Decision-making Trial And Evaluation LaboratoryFuzzy Group Decision MakingFuzzy Multi-criteria Decision AnalysisFuzzy NumbersFuzzy SetsLinguistic VariablesMulti-criteria Group Decision Making
The fuzzy decision-making trial and evaluation laboratory (fuzzy DEMATEL) has been used to solve various multi-criteria group decision-making problems where triangular fuzzy numbers are utilized in defining decision makers’ linguistic judgements. Most of the fuzzy DEMATEL modifications are built from linguistic variables based on fuzzy sets. Recent literature suggests that Pythagorean fuzzy sets (PFS) can offer a better alternative particularly when fuzzy sets have some extent of limitations in handling vagueness and uncertainty. This paper proposes a modification fuzzy DEMATEL characterized by PFS for linguistic variables. Differently from the typical fuzzy DEMATEL which directly utilizes triangular fuzzy numbers with a single membership, this modification introduces membership and non-membership of PFS to enhance judgements in the group decision-making environment. The proposed method has a number of attractive features. It includes linguistic variables, expert’s weights, and score function, in which all of these features are expressed by PFS. The proposed modification is applied to a case of solid waste management (SWM) where ten criteria are considered in assessment. Six experts in SWM were invited to provide linguistic judgments with respect to the criteria, and the eleven-step computational procedure of the proposed method was implemented without losing the general structure of the DEMATEL method. The results unveiled that four criteria are identified as ‘cause group’ and six criteria are identified as ‘effect group’ in SWM. The grouping of criteria would help policy makers in identifying the criteria that could enhance the efficiency of SWM.
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L. A. Zadeh · Information and Control · 1965 · 66.1K citations
Krassimir Atanassov · Fuzzy Sets and Systems · 1986 · 16.2K citations · Full text
Some Results for Pythagorean Fuzzy Sets
Xindong Peng, Yong Yang · International Journal of Intelligent Systems · 2015 · 852 citations