On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Fuzzy Sets and Systems
Measures of entropy and fuzziness related to aggregation operators
Information Sciences—Intelligent Systems: An International Journal
On the issue of obtaining OWA operator weights
Fuzzy Sets and Systems
An analytic approach for obtaining maximal entropy OWA operator weights
Fuzzy Sets and Systems
On obtaining minimal variability OWA operator weights
Fuzzy Sets and Systems - Theme: Multicriteria decision
A minimax disparity approach for obtaining OWA operator weights
Information Sciences: an International Journal
International Journal of Intelligent Systems
An extended minimax disparity to determine the OWA operator weights
Computers and Industrial Engineering
Two new models for determining OWA operator weights
Computers and Industrial Engineering
Notes on properties of the OWA weights determination model
Computers and Industrial Engineering
OWA operators with maximal Rényi entropy
Fuzzy Sets and Systems
On the properties of OWA operator weights functions with constant level of orness
IEEE Transactions on Fuzzy Systems
Maximum Bayesian entropy method for determining ordered weighted averaging operator weights
Computers and Industrial Engineering
Determining OWA operator weights by mean absolute deviation minimization
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
Determination of Ordered Weighted Averaging Operator Weights Based on the M-Entropy Measures
International Journal of Intelligent Systems
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It has a wide attention about the methods for determining OWA operator weights. At the beginning of this dissertation, we provide a briefly overview of the main approaches for obtaining the OWA weights with a predefined degree of orness. Along this line, we next make an important generalization of these approaches as a special case of the well-known and more general problem of calculation of the probability distribution in the presence of uncertainty. All these existed methods for dealing these kinds of problems are quite complex. In order to simplify the process of computation, we introduce Yager's entropy based on Minkowski metric. By analyzing its desirable properties and utilizing this measure of entropy, a linear programming (LP) model for the problem of OWA weight calculation with a predefined degree of orness has been built and can be calculated much easier. Then, this result is further extended to the more realistic case of only having partial information on the range of OWA weights except a predefined degree of orness. In the end, two numerical examples are provided to illustrate the application of the proposed approach.