Choosing OWA operator weights in the field of Social Choice

Information Sciences

Volumn 177, Issue 21, 2007, Pages 4745-4756

  Llamazares, Bonifacio ^a  

^a UNIVERSITY OF VALLADOLID   (Spain)

Author keywords

Aggregation operator weights; Majority rules; Ordered weighted averaging operators

Indexed keywords

INFORMATION THEORY; MATHEMATICAL MODELS;

AGGREGATION OPERATOR WEIGHTS; MAJORITY RULES; ORDERED WEIGHTED AVERAGING OPERATORS;

MATHEMATICAL OPERATORS;

EID: 34547793584     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2007.05.015     Document Type: Article

References (36)

1. Amin G.R., and Emrouznejad A. An extended minimax disparity to determine the OWA operator weights. Computers & Industrial Engineering 50 (2006) 312-316
2. In: Calvo T., Mayor G., and Mesiar R. (Eds). Aggregation Operators: New Trends and Applications (2002), Physica-Verlag, Heidelberg
3. Filev D., and Yager R.R. On the issue of obtaining OWA operator weights. Fuzzy Sets and Systems 94 (1998) 157-169
4. Fullér R., and Majlender P. An analytic approach for obtaining maximal entropy OWA operator weights. Fuzzy Sets and Systems 124 (2001) 53-57
5. Fullér R., and Majlender P. On obtaining minimal variability OWA operator weights. Fuzzy Sets and Systems 136 (2003) 203-215
6. García Lapresta J.L. A general class of simple majority decision rules based on linguistic opinions. Information Sciences 176 (2006) 352-365
7. García Lapresta J.L., and Llamazares B. Aggregation of fuzzy preferences: some rules of the mean. Social Choice and Welfare 17 (2000) 673-690
8. García Lapresta J.L., and Llamazares B. Majority decisions based on difference of votes. Journal of Mathematical Economics 35 (2001) 463-481
9. Liu X. On the properties of equidifferent OWA operator. International Journal of Approximate Reasoning 43 (2006) 90-107
10. Liu X., and Chen L. On the properties of parametric geometric OWA operator. International Journal of Approximate Reasoning 35 (2004) 163-178
11. Liu X., and Lou H. Parameterized additive neat OWA operators with different orness levels. International Journal of Intelligent Systems 21 (2006) 1045-1072
12. Llamazares B. Simple and absolute special majorities generated by OWA operators. European Journal of Operational Research 158 (2004) 707-720
13. Llamazares B. The forgotten decision rules: majority rules based on difference of votes. Mathematical Social Sciences 51 (2006) 311-326
14. Maes K.C., Saminger S., and De Baets B. Representation and construction of self-dual aggregation operators. European Journal of Operational Research 177 (2007) 472-487
15. Majlender P. OWA operators with maximal Rényi entropy. Fuzzy Sets and Systems 155 (2005) 340-360
16. J.L. Marichal, Aggregation Operators for Multicriteria Decision Aid, MA thesis, Liège University, Liège, 1998.
17. Nettleton D., and Torra V. A comparison of active set method and genetic algorithm approaches for learning weighting vectors in some aggregation operators. International Journal of Intelligent Systems 16 (2001) 1069-1083
18. M. O'Hagan, Aggregating template or rule antecedents in real-time expert systems with fuzzy set logic, in: Proc. 22nd Annual IEEE Asilomar Conf. on Signals, Systems and Computers, Pacific Grove, California, 1988, pp. 681-689.
19. Pasi G., and Yager R.R. Modeling the concept of majority opinion in group decision making. Information Sciences 176 (2006) 390-414
20. Peláez J.I., and Doña J.M. A majority model in group decision making using QMA-OWA operators. International Journal of Intelligent Systems 21 (2006) 193-208
21. Wang Y.M., and Parkan C. A minimax disparity approach for obtaining OWA operator weights. Information Sciences 175 (2005) 20-29
22. Wang Y.M., and Parkan C. Two new approaches for assessing the weights of fuzzy opinions in group decision analysis. Information Sciences 176 (2006) 3538-3555
23. Wang Y.M., and Parkan C. A preemptive goal programming method for aggregating OWA operator weights in group decision making. Information Sciences 177 (2007) 1867-1877
24. Xu Z.S. A method based on linguistic aggregation operators for group decision making with linguistic preference relations. Information Sciences 166 (2004) 19-30
25. Xu Z.S. An overview of methods for determining OWA weights. International Journal of Intelligent Systems 20 (2005) 843-865
26. Xu Z.S. Dependent OWA operators. In: Torra V., Narukawa Y., Valls A., and Domingo-Ferrer J. (Eds). Modeling Decisions for Artificial Intelligence: Third International Conference MDAI 2006. Lecture Notes in Artificial Intelligence vol. 3885 (2006), Springer, Berlin 172-178
27. Xu Z.S., and Da Q.L. The uncertain OWA operator. International Journal of Intelligent Systems 17 (2002) 569-575
28. Xu Z.S., and Da Q.L. An overview of operators for aggregating information. International Journal of Intelligent Systems 18 (2003) 953-969
29. Yager R.R. On ordered weighted averaging operators in multicriteria decision making. IEEE Transactions on Systems, Man and Cybernetics 18 (1988) 183-190
30. Yager R.R. Families of OWA operators. Fuzzy Sets and Systems 59 (1993) 125-148
31. Yager R.R. Quantifier guided aggregation using OWA operators. International Journal of Intelligent Systems 11 (1996) 49-73
32. R.R. Yager, E-Z OWA weights, in: Proc. 10th International Fuzzy Systems Association World Congress, Istanbul, 2003, pp. 39-42.
33. Yager R.R. Extending multicriteria decision making by mixing t-norms and OWA operators. International Journal of Intelligent Systems 20 (2005) 453-474
34. Yager R.R. Centered OWA operators. Soft Computing 11 (2007) 631-639
35. Yager R.R., and Filev D. Induced ordered weighted averaging operators. IEEE Transactions on Systems, Man and Cybernetics - Part B: Cybernetics 29 (1999) 141-150
36. In: Yager R.R., and Kacprzyk J. (Eds). The Ordered Weighted Averaging Operators: Theory and Applications (1997), Kluwer Academic Publishers, Dordrecht