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
Using classification as an aggregation tool in MCDM
Fuzzy Sets and Systems - Special issue on soft decision analysis
Dual Stochastic Dominance and Related Mean-Risk Models
SIAM Journal on Optimization
Minimizing the sum of the k largest functions in linear time
Information Processing Letters
A minimax disparity approach for obtaining OWA operator weights
Information Sciences: an International Journal
Modeling Decisions: Information Fusion and Aggregation Operators (Cognitive Technologies)
Modeling Decisions: Information Fusion and Aggregation Operators (Cognitive Technologies)
An extended minimax disparity to determine the OWA operator weights
Computers and Industrial Engineering
Notes on properties of the OWA weights determination model
Computers and Industrial Engineering
Preference relation approach for obtaining OWA operators weights
International Journal of Approximate Reasoning
On optimization of the importance weighted OWA aggregation of multiple criteria
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part I
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
Parameterized OWA operator weights: An extreme point approach
International Journal of Approximate Reasoning
LP Solvable Models for Multiagent Fair Allocation Problems
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Multicriteria subjective reputation management model
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
Hesitant fuzzy information aggregation in decision making
International Journal of Approximate Reasoning
Computing rank dependent utility in graphical models for sequential decision problems
Artificial Intelligence
On distorted probabilities and m-separable fuzzy measures
International Journal of Approximate Reasoning
Exact algorithms for OWA-optimization in multiobjective spanning tree problems
Computers and Operations Research
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
Compact versus noncompact LP formulations for minimizing convex Choquet integrals
Discrete Applied Mathematics
MDAI'12 Proceedings of the 9th international conference on Modeling Decisions for Artificial Intelligence
Minimizing ordered weighted averaging of rational functions with applications to continuous location
Computers and Operations Research
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The problem of averaging outcomes under several scenarios to form overall objective functions is of considerable importance in decision support under uncertainty. The so-called Weighted OWA (WOWA) aggregation offers a well-suited approach to this problem. The WOWA aggregation, similar to the classical ordered weighted averaging (OWA), uses the preferential weights assigned to the ordered values (i.e. to the worst value, the second worst and so on) rather than to the specific criteria. This allows one to model various preferences with respect to the risk. Simultaneously, importance weighting of scenarios can be introduced. In this paper, we analyze solution procedures for optimization problems with the WOWA objective functions related to decisions under risk. Linear programming formulations are introduced for optimization of the WOWA objective with monotonic preferential weights thus representing risk averse preferences. Their computational efficiency is demonstrated.