Extensions of the analytic hierarchy process in fuzzy environment
Fuzzy Sets and Systems
Aggregation of partial ordinal rankings: an interval goal programming approach
Computers and Operations Research
On Compatibility of Interval Fuzzy Preference Relations
Fuzzy Optimization and Decision Making
Information Sciences—Informatics and Computer Science: An International Journal
A preference aggregation method through the estimation of utility intervals
Computers and Operations Research
An approach to solve group-decision-making problems with ordinal interval numbers
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An extended TOPSIS for determining weights of decision makers with interval numbers
Knowledge-Based Systems
A hybrid approach based on SERVQUAL and fuzzy TOPSIS for evaluating transportation service quality
Computers and Industrial Engineering
A 2-tuple fuzzy linguistic representation model for computing with words
IEEE Transactions on Fuzzy Systems
A method based on shape-similarity for detecting similar opinions in group decision-making
Information Sciences: an International Journal
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In group decision making under uncertainty, interval preference orderings as a type of simple uncertain preference structure, can be easily and conveniently used to express the experts' evaluations over the considered alternatives. In this paper, we investigate group decision making problems with interval preference orderings on alternatives. We start by fusing all individual interval preference orderings given by the experts into the collective interval preference orderings through the uncertain additive weighted averaging operator. Then we establish a nonlinear programming model by minimizing the divergences between the individual uncertain preferences and the group's opinions, from which we derive an exact formula to determine the experts' relative importance weights. After that, we calculate the distances of the collective interval preference orderings to the positive and negative ideal solutions, respectively, based on which we use a TOPSIS based approach to rank and select the alternatives. All these results are also reduced to solve group decision making problems where the experts' evaluations over the alternatives are expressed in exact preference orderings. A numerical analysis of our model and approach is finally carried out using two illustrative examples.