The results in this paper are helpful to complete Chiclana et al.'s fuzzy decision model [Integrating three representation models in fuzzy multipurpose decision making based on fuzzy preference relations, Fuzzy Sets and Systems 97 (1998 33 48]].
The subsequent contraction of the decision uncertainty regions is associated with reduction of the problem to multiobjective decision making in a fuzzy environment with using techniques based on fuzzy preference relations.
According to theory and method of group decision making, the method and procedure of the industry selection are proposed based on fuzzy preference relations and C-IOWA operator, which reduces the objective of the experts in the process of industry selection, so as to enhance the efficiency and quality of it.
The conversion approach introduced is based on fuzzy linguistic preferences of DM, in addition to the concepts of conflict analysis among objective functions and fuzzy set theory.
A new fuzzy operator, namely, the unified AND OR (UAO) operator is also proposed, and a decision-making approach based on fuzzy rules and preference rules is introduced.
The aims of this study were (1) to classify collected Kansei words into a set of Kansei attributes by using cluster analysis based on fuzzy relations; (2) to model Kansei preferences based on semantic labels for the priority analysis; and (3) to synthesize priority information and rank the order of decision alternatives by means of the linguistic aggregation operation.
Our work in [13] is a direction based on fuzzy logic to take user scalability preferences into account for a cloud setting.
As a consequence, a selection process based on fuzzy majority for multipurpose decision-making problems under multiplicative preference relations is presented.
A solution is extracted to eliminate the imprecise nature of preference through the Pareto optimal set based on fuzzy set theory.
To this scope, all the previously mentioned parameters are evaluated following a mathematical approach based on Fuzzy Logic and are aggregated using the 'Technique for Order Preference by Similarity to Ideal Solution TOPSISIS) to define the resulting critical path.
