On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Essentials of fuzzy modeling and control
Essentials of fuzzy modeling and control
Fuzzy Sets and Systems - Special issue on fuzzy optimization
The ordered weighted averaging operators: theory and applications
The ordered weighted averaging operators: theory and applications
Fuzzy aggregation of numerical preferences
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Fuzzy Sets and Systems - Special issue on soft decision analysis
A WOWA-based Aggregation Technique on Trust Values Connected to Metadata
Electronic Notes in Theoretical Computer Science (ENTCS)
Some properties of the weighted OWA operator
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Including importances in OWA aggregations using fuzzy systems modeling
IEEE Transactions on Fuzzy Systems
WOWA Enhancement of the Preference Modeling in the Reference Point Method
MDAI '08 Sabadell Proceedings of the 5th International Conference on Modeling Decisions for Artificial Intelligence
On efficient WOWA optimization for decision support under risk
International Journal of Approximate Reasoning
On Principles of Fair Resource Allocation for Importance Weighted Agents
SOCINFO '09 Proceedings of the 2009 International Workshop on Social Informatics
On ordered weighted reference point model for multi-attribute procurement auctions
ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part I
MDAI'12 Proceedings of the 9th international conference on Modeling Decisions for Artificial Intelligence
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The problem of aggregating multiple numerical criteria to form overall objective functions is of considerable importance in many disciplines. The ordered weighted averaging (OWA) aggregation, introduced by Yager, uses the weights assigned to the ordered values rather than to the specific criteria. This allows one to model various aggregation preferences, preserving simultaneously the impartiality (neutrality) with respect to the individual criteria. However, importance weighted averaging is a central task in multicriteria decision problems of many kinds. It can be achieved with the Weighted OWA (WOWA) aggregation though the importance weights make the WOWA concept much more complicated than the original OWA. We show that the WOWA aggregation with monotonic preferential weights can be reformulated in a way allowing to introduce linear programming optimization models, similar to the optimization models we developed earlier for the OWA aggregation. Computational efficiency of the proposed models is demonstrated.