Skip to main content

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 265))

Abstract

The OWA operator determination is an important prerequisite step for OWA operator applications. With the application of OWA operator in various areas, the OWA operator determination becomes an active topic in recent years. Based on recent developments, the paper give a summary on the OWA determination methods in classification way: the optimization criteria methods, the sample learning methods, the function based methods, the argument dependent methods and the preference methods. Some relationships between the methods in the same kind and the relationships between different kinds are provided. An uniform framework to connect these OWA determination methods together is also attempted. Some extensions, problems and future research directions are given with discussions.

The work is supported by the National Natural Science Foundation of China (NSFC) under project 70771025, and Program for New Century Excellent Talents in University of China NCET-06-0467.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ahn, B.S.: On the properties of OWA operator weights functions with constant level of orness. IEEE Transactions on Fuzzy Systems 14(4), 511–515 (2006)

    Article  Google Scholar 

  2. Ahn, B.S.: Preference relation approach for obtaining OWA operators weights. International Journal of Approximate Reasoning 47(2), 166–178 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  3. Ahn, B.S., Park, H.: An efficient pruning method for decision alternatives of OWA operators. IEEE Transactions On Fuzzy Systems 16(6), 1542–1549 (2008)

    Article  Google Scholar 

  4. Ahn, B.S., Park, H.: Least-squared ordered weighted averaging operator weights. International Journal of Intelligent Systems 23(1), 33–49 (2008)

    Article  MATH  Google Scholar 

  5. Amin, G.R.: Note on A preemptive goal programming method for aggregating OWA operator weights in group decision making. Information Sciences 177(17), 3636–3638 (2007)

    Article  MATH  Google Scholar 

  6. Amin, G.R.: Notes on properties of the OWA weights determination model. Computers & Industrial Engineering 52(4), 533–538 (2007)

    Article  Google Scholar 

  7. Amin, G.R., Emrouznejad, A.: An extended minimax disparity to determine the OWA operator weights. Computers and Industrial Engineering 50(3), 312–316 (2006)

    Article  Google Scholar 

  8. Beliakov, G.: Methods of construction of OWA operators from data. In: IEEE International Conference on Fuzzy Systems, Melbourne, vol. 1 (2001)

    Google Scholar 

  9. Beliakov, G.: How to build aggregation operators from data. International Journal of Intelligent Systems 18(8), 903–923 (2003)

    Article  MATH  Google Scholar 

  10. Beliakov, G.: Learning weights in the generalized OWA operators. Fuzzy Optimization and Decision Making 4, 119–130 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  11. Beliakov, G., Mesiar, R., Valaskova, L.: Fitting generated aggregation operators to empirical data. International Journal Of Uncertainty Fuzziness And Knowledge-Based Systems 12(2), 219–236 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  12. Beliakov, G., Pradera, A., Calvo, T.: Aggregation Functions: A Guide for Practitioners. Springer, Heidelberg (2007)

    Google Scholar 

  13. Boongoen, T., Shen, Q.: Clus-DOWA: A new dependent OWA operator. In: IEEE International Conference on Fuzzy Systems. IEEE, Hong Kong

    Google Scholar 

  14. Carbonell, M., Mas, M., Mayor, G.: On a class of monotonic extended OWA operators. In: The Sixth IEEE International Conference on Fuzzy Systems, Barcelona (1997)

    Google Scholar 

  15. Chakraborty, C., Chakraborty, D.: A decision scheme based on owa operator for an evaluation programme: an approximate reasoning approach. Applied Soft Computing 5(1), 45–53 (2004)

    Article  Google Scholar 

  16. Cheng, C.H., Chang, J.R.: MCDM aggregation model using situational ME-OWA and ME-OWGA operators. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems 14(4), 421–443 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  17. Chiclana, F., Herrera, F., Herrera-Viedma, E., Martínez, L.: A note on the reciprocity in the aggregation of fuzzy preference relations using OWA operators. Fuzzy Sets and Systems 137(1), 71–83 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  18. Emrouznejad, A.: MP-OWA: The most preferred OWA operator. Knowledge-Based Systems 21, 847–851 (2008)

    Article  Google Scholar 

  19. Filev, D., Yager, R.R.: Analytic properties of maximum entropy OWA operators. Information Sciences 85(1-3), 11–27 (1995)

    Article  MATH  Google Scholar 

  20. Filev, D., Yager, R.R.: On the issue of obtaining OWA operator weights. Fuzzy Sets and Systems 94(2), 157–169 (1998)

    Article  MathSciNet  Google Scholar 

  21. Fullér, R., Majlender, P.: An analytic approach for obtaining maximal entropy OWA operator weights. Fuzzy Sets and Systems 124(1), 53–57 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  22. Fullér, R., Majlender, P.: On obtaining minimal variability OWA operator weights. Fuzzy Sets and Systems 136(2), 203–215 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  23. Herrera, F., Herrera-Viedma, E., Chiclana, F.: A study of the origin and uses of the ordered weighted geometric operator in multicriteria decision making. International Journal of Intelligent Systems 18(6), 689–707 (2003)

    Article  MATH  Google Scholar 

  24. Herrera, F., Herrera-Viedma, E., Verdegay, J.: Direct approach processes in group decision making using linguistic OWA operators. Fuzzy Sets and Systems 79(2), 175–190 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  25. Herrera-Viedma, E., Cordón, O., Luque, M., Lopez, A.G., Muñoz, A.M.: A model of fuzzy linguistic IRS based on multi-granular linguistic information. International Journal of Approximate Reasoning 34(2-3), 221–239 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  26. Kacprzyk, J., Zadrozny, S.: Computing with words in intelligent database querying: standalone and internet-based applications. Information Sciences 134(1), 71–109 (2001)

    Article  MATH  Google Scholar 

  27. Kacprzyk, J., Zadrożny, S., Fedrizzi, M., Nurmi, H.: On group decision making, consensus reaching, voting and voting paradoxes under fuzzy preferences and a fuzzy majority: A survey and some perspectives. In: Bustince, H., Herrera, F., Montero, J. (eds.) Fuzzy Sets and Their Extensions: Representation, Aggregation and Models. Springer, Heidelberg (2008)

    Google Scholar 

  28. Liu, X.: Parameterized OWA operator determination with optimization criteria: A general model, submitted to Information Sciences

    Google Scholar 

  29. Liu, X.: The relationships between two kinds of variability optimization and orness optimization problems for OWA operator with their RIM quantifier extensions. International Journal of General Systems (2008) (accpeted)

    Google Scholar 

  30. Liu, X.: On the properties of equidifferent RIM quantifier with generating function. International Journal of General Systems 34(5), 579–594 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  31. Liu, X.: On the properties of equidifferent OWA operator. International Journal of Approximate Reasoning 43(1), 90–107 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  32. Liu, X.: Some properties of the weighted OWA operator. IEEE Transactions on Systems, Man and Cybernetics, Part B 36(1), 118–127 (2006)

    Google Scholar 

  33. Liu, X.: The solution equivalence of minimax disparity and minimum variance problems for OWA operator. International Journal of Approximate Reasoning 45(1), 68–81 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  34. Liu, X.: A general model of parameterized OWA aggregation with given orness level. International Journal of Approximate Reasoning 48(2), 598–627 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  35. Liu, X.: On the properties of regular increasing monotone RIM quantifiers with maximum entropy. International Journal of General Systems 37(2), 167–179 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  36. Liu, X., Chen, L.: On the properties of parametric geometric OWA operator. International Journal of Approximate Reasoning 35(2), 163–178 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  37. Liu, X., Han, S.: Orness and parameterized RIM quantifier aggregation with OWA operators: A summary. International Journal of Approximate Reasoning 48(1), 77–97 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  38. Liu, X., Lou, H.: Parameterized additive neat OWA operators with different orness levels. International Journal of Intelligent Systems 21(10), 1045–1072 (2006)

    Article  MATH  Google Scholar 

  39. Liu, X., Yang, X., Fang, Y.: The relationships between two kinds of OWA operator determination methods. In: IEEE International Conference on Fuzzy Systems, Hong Kong

    Google Scholar 

  40. Llamazares, B.: Choosing OWA operator weights in the field of social choice. Information Sciences 177(21), 4745–4756 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  41. Majlender, P.: OWA operators with maximal Rényi entropy. Fuzzy Sets and Systems 155(3), 340–360 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  42. Marchant, T.: Maximal orness weights with a fixed variability for OWA operators. International Journal of Uncertainty, Fuzziness Knowledge-Based Systems 14(3), 271–276 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  43. Marimin, M., Umano, M., Hatono, I., Tamura, H.: Linguistic labels for expressing fuzzy preference relations in fuzzy group decision making. IEEE Transactions on Systems, Man and Cybernetics, Part B 28(2), 205–218 (1998)

    Article  Google Scholar 

  44. Marimin, M., Umano, M., Hatono, I., Tamura, H.: Hierarchical semi-numeric method for pairwise fuzzy group decision making. IEEE Transactions on Systems, Man and Cybernetics, Part B 32(5), 691–700 (2002)

    Article  Google Scholar 

  45. Merigo, J.M., Gil-Lafuente, A.M.: The induced generalized OWA operator. Information Sciences 179(6), 729–741 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  46. O’Hagan, M.: Aggregating template or rule antecedents in real-time expert systems with fuzzy set. In: Grove, P. (ed.) Proc. 22nd Annu. IEEE Asilomar Conf. on Signals, Systems, Computers, CA (1988)

    Google Scholar 

  47. Peláez, J.I., Doña, J.M.: Majority additive-ordered weighting averaging: a new neat ordered weighting averaging operator based on the majority process. International Journal of Intelligent Systems 18, 469–481 (2003)

    Article  MATH  Google Scholar 

  48. Peláez, J.I., Doña, J.M.: A majority model in group decision making using QMA-OWA operators. International Journal of Intelligent Systems 21(2), 193–208 (2006)

    Article  MATH  Google Scholar 

  49. Peláez, J.I., Doña, J.M., Gómez-Ruiz, J.A.: Analysis of OWA operators in decision making for modelling the majority concept. Applied Mathematics and Computation (New York) 186(2), 1263–1275 (2007)

    Article  MATH  Google Scholar 

  50. Renaud, J., Levrat, E., Fonteix, C.: Weights determination of OWA operators by parametric identification. Mathematics and Computers in Simulation 77(5-6), 499–511 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  51. Sadiq, R., Tesfamariam, S.: Probability density functions based weights for ordered weighted averaging (OWA) operators: An example of water quality indices. European Journal of Operational Research 182(3), 1350–1368 (2007)

    Article  MATH  Google Scholar 

  52. Sicilia, M.-A., García-Barriocanal, E., Sánchez-Alonso, S.: Empirical assessment of a collaborative filtering algorithm based on OWA operators. International Journal of Intelligent Systems 23, 1251–1263 (2008)

    Article  MATH  Google Scholar 

  53. Torra, V.: The weighted OWA operator. International Journal of Intelligent Systems 12(2), 153–166 (1997)

    Article  MATH  Google Scholar 

  54. Torra, V.: Learning weights for weighted OWA operators. In: 26th Annual Confjerence of the IEEE Industrial Electronics Society, vol. 4 (2000)

    Google Scholar 

  55. Torra, V.: Learning weights for the quasi-weighted means. IEEE Transactions on Fuzzy Systems 10(5), 653–666 (2002)

    Article  MathSciNet  Google Scholar 

  56. Torra, V.: OWA operators in data modeling and reidentification. IEEE Transactions on Fuzzy Systems 12(5), 652–660 (2004)

    Article  Google Scholar 

  57. Wang, J.W., Chang, J.R., Cheng, C.H.: Flexible fuzzy OWA querying method for hemodialysis database. Soft Computing 10(11), 1031–1042 (2006)

    Article  Google Scholar 

  58. Wang, Y., Luo, Y., Hua, Z.: Aggregating preference rankings using OWA operator weights. Information Sciences 177(16), 3356–3363 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  59. Wang, Y., Luo, Y., Liu, X.: Two new models for determining OWA operator weights. Computers and Industrial Engineering 52, 203–209 (2007)

    Article  Google Scholar 

  60. Wang, Y., Parkan, C.: A minimax disparity approach for obtaining OWA operator weights. Information Sciences 175(1), 20–29 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  61. Wang, Y., Parkan, C.: A preemptive goal programming method for aggregating OWA operator weights in group decision making. Information Sciences 177, 1867–1877 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  62. Wu, J., Liang, C.Y., Huang, Y.Q.: An argument-dependent approach to determining OWA operator weights based on the rule of maximum entropy. International Journal of Intelligent Systems 22(2), 209–221 (2007)

    Article  MATH  Google Scholar 

  63. Wu, J., Sun, B.-L., Liang, C.-Y., Yang, S.-L.: A linear programming model for determining ordered weighted averaging operator weights with maximal yager’s entropy. Computers & Industrial Engineering (2009), doi:10.1016/j.cie.2009.02.001

    Google Scholar 

  64. Xu, Z.S.: Dependent OWA operators. In: Torra, V., Narukawa, Y., Valls, A., Domingo-Ferrer, J. (eds.) MDAI 2006. LNCS (LNAI), vol. 3885, pp. 172–178. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  65. Xu, Z.S.: An overview of methods for determining OWA weights. International Journal of Intelligent Systems 20(8), 843–865 (2005)

    Article  MATH  Google Scholar 

  66. Xu, Z.S., Da, Q.L.: The ordered weighted geometric averaging operators. International Journal of Intelligent Systems 17(7), 709–716 (2002)

    Article  MATH  Google Scholar 

  67. Xu, Z.S., Da, Q.L.: Approaches to obtaining the weights of the ordered weighted aggregation operators. Journal of Southeast University 33, 94–96 (2003)

    MathSciNet  Google Scholar 

  68. Yager, R.R.: On ordered weighted averaging aggregation operators in multicriteria decision making. IEEE Transactions on Systems, Man and Cybernetics 18(1), 183–190 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  69. Yager, R.R.: Families of OWA operators. Fuzzy Sets and Systems 59(2), 125–143 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  70. Yager, R.R.: Quantifier guided aggregation using OWA operators. International Journal of Intelligent Systems 11(1), 49–73 (1996)

    Article  Google Scholar 

  71. Yager, R.R.: On the analytic representation of the Leximin ordering and its application to flexible constraint propagation. European Journal of Operational Research 102(1), 176–192 (1997)

    Article  MATH  Google Scholar 

  72. Yager, R.R.: Fuzzy modeling for intelligent decision making under uncertainty. IEEE Transactions on Systems, Man and Cybernetics, Part B 30(1), 60–70 (2000)

    Article  Google Scholar 

  73. Yager, R.R.: A hierarchical document retrieval language. Information Retrieval 3(4), 357–377 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  74. Yager, R.R.: On the valuation of alternatives for decision-making under uncertainty. International Journal of Intelligent Systems 17(7), 687–707 (2002)

    Article  MATH  Google Scholar 

  75. Yager, R.R.: Toward a language for specifying summarizing statistics. IEEE Transactions on Systems, Man and Cybernetics, Part B 33(2), 177–187 (2003)

    Article  Google Scholar 

  76. Yager, R.R.: OWA aggregation over a continuous interval argument with applications to decision making. IEEE Transactions on Systems, Man and Cybernetics, Part B 34(5), 1952–1963 (2004)

    Article  Google Scholar 

  77. Yager, R.R.: An extension of the naive bayesian classifier. Information Sciences 176(5), 577–588 (2006)

    Article  MathSciNet  Google Scholar 

  78. Yager, R.R.: Centered OWA operators. Soft Computing 11(7), 631–639 (2007)

    Article  MATH  Google Scholar 

  79. Yager, R.R.: Using stress functions to obtain OWA operators. IEEE Transactions on Fuzzy Systems 15(6), 1122–1129 (2007)

    Article  MathSciNet  Google Scholar 

  80. Yager, R.R.: Time series smoothing and OWA aggregation. IEEE Transactions on Fuzzy Systems 16(4), 994–1007 (2008)

    Article  Google Scholar 

  81. Yager, R.R., Filev, D.P.: Parameterized and-like and or-like OWA operators. International Journal of General Systems 22(3), 297–316 (1994)

    Article  Google Scholar 

  82. Yager, R.R., Filev, D.P.: Induced ordered weighted averaging operators. IEEE Transactions on Systems, Man and Cybernetics, Part B 29(2), 141–150 (1999)

    Article  Google Scholar 

  83. Yager, R.R., Kacprzyk, J.: The ordered weighted averaging operators—Theory and applications. Kluwer Academic Publishers, Dordrecht (1997)

    Google Scholar 

  84. Zadrozny, S., Kacprzyk, J.: Computing with words for text processing: An approach to the text categorization. Information Sciences 176(4), 415–437 (2006)

    Article  MathSciNet  Google Scholar 

  85. Zadrożny, S., Kacprzyk, J.: On tuning OWA operators in a flexible querying interface. In: Larsen, H.L., Pasi, G., Ortiz-Arroyo, D., Andreasen, T., Christiansen, H. (eds.) FQAS 2006. LNCS (LNAI), vol. 4027, pp. 97–108. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Liu, X. (2011). A Review of the OWA Determination Methods: Classification and Some Extensions. In: Yager, R.R., Kacprzyk, J., Beliakov, G. (eds) Recent Developments in the Ordered Weighted Averaging Operators: Theory and Practice. Studies in Fuzziness and Soft Computing, vol 265. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17910-5_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-17910-5_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17909-9

  • Online ISBN: 978-3-642-17910-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics