Quantifiers in the formulation of multiple objective decision functions
Information Sciences: an International Journal
On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Connectives and quantifiers in fuzzy sets
Fuzzy Sets and Systems - Special memorial volume on foundations of fuzzy reasoning
Fuzzy Sets and Systems
OWA operators for doctoral student selection problem
The ordered weighted averaging operators
Aggregation operators for selection problems
Fuzzy Sets and Systems - Special issue: Soft decision analysis
Fuzzy Sets and Systems - Optimisation and decision
Orness and parameterized RIM quantifier aggregation with OWA operators: A summary
International Journal of Approximate Reasoning
Fuzzy quantifiers in sensitivity analysis of OWA operator
Computers and Industrial Engineering
A general model of parameterized OWA aggregation with given orness level
International Journal of Approximate Reasoning
Algorithms for fuzzy multi expert multi criteria decision making (ME-MCDM)
Knowledge-Based Systems
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Developments in Multi-Criteria (MCDM) and Multi-Expert decision-making allow for using linguistic quantifiers such as 'all', 'most', 'at least half' and similar terms as quantifiers for the decision. Additionally, new methods of aggregating the various opinions have been developed, giving the decision maker an increasingly large variety of options.This paper presents the concept of linguistic quantifiers and presents a collection of quantifiers with their associated weight functions. This paper explores the effect that the type of linguistic quantifier and the aggregation method used have on the ranking of alternatives. This study utilizes eleven linguistic quantifiers and four aggregation means using four well-documented MCDM problems.The results show that the effect of the linguistic quantifiers varies and some quantifiers have more impact on ranking of the alternatives then others. Additionally, the sensitivity of the decision made to the aggregation method is found to be relatively small. The study finds that the weighted harmonic mean is the most sensitive aggregation function to the changes of linguistic quantifiers. The results of this research allow the decision maker to choose the linguistic quantifier and aggregation method based on subjective belief without impeding the resulting decision.