Skip to main content

Maximal Entropy and Minimal Variability OWA Operator Weights: A Short Survey of Recent Developments

  • Chapter
  • First Online:
Soft Computing Applications for Group Decision-making and Consensus Modeling

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 357))

Abstract

The determination of ordered weighted averaging (OWA) operator weights is a very important issue of applying the OWA operator for decision making. One of the first approaches, suggested by O’Hagan, determines a special class of OWA operators having maximal entropy of the OWA weights for a given level of orness; algorithmically it is based on the solution of a constrained optimization problem. In 2001, using the method of Lagrange multipliers, Fullér and Majlender solved this constrained optimization problem analytically and determined the optimal weighting vector. In 2003 Fullér and Majlender computed the exact minimal variability weighting vector for any level of orness using the Karush-Kuhn-Tucker second-order sufficiency conditions for optimality. The problem of maximizing an OWA aggregation of a group of variables that are interrelated and constrained by a collection of linear inequalities was first considered by Yager in 1996, where he showed how this problem can be modeled as a mixed integer linear programming problem. In 2003 Carlsson, Fullér and Majlender derived an algorithm for solving the constrained OWA aggregation problem under a simple linear constraint: the sum of the variables is less than or equal to one. In this paper we give a short survey of numerous later works which extend and develop these models.

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 EPUB and 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

References

  1. Aggarwal M (2015) On learning of weights through preferences. Inf Sci 321:90–102

    Article  MathSciNet  Google Scholar 

  2. Ahn BS (2008) Some quantier functions from weighting functions with constant value of orness. IEEE Trans Syst Man Cybern Part B 38:540–546

    Article  Google Scholar 

  3. Ahn BS (2009) Some remarks on the LSOWA approach for obtaining OWA operator weights. Int J Intell Syst 24(12):1265–1279

    Google Scholar 

  4. Ahn BS (2010) Parameterized OWA operator weights: an extreme point approach. Int J Approx Reason 51:820–831

    Article  MATH  Google Scholar 

  5. Ahn BS (2011) Compatible weighting method with rank order centroid: maximum entropy ordered weighted averaging approach. Eur J Oper Res 212:552–559

    Article  MathSciNet  MATH  Google Scholar 

  6. Amin GR, Emrouznejad A (2006) An extended minimax disparity to determine the OWA operator weights. Comput Ind Eng 50:312–316

    Article  Google Scholar 

  7. Carlsson C, Fullér R, Majlender P (2003) A note on constrained OWA aggregations. Fuzzy Sets Syst 139:543–546

    Article  MathSciNet  MATH  Google Scholar 

  8. Carlsson C, Fedrizzi M, Fullér R (2004) Fuzzy logic in management. International series in operations research and management science, vol 66. Kluwer Academic Publishers, Boston

    MATH  Google Scholar 

  9. Chaji A (2017) Analytic approach on maximum Bayesian entropy ordered weighted averaging operators. Comput Ind Eng 105:260–264

    Article  Google Scholar 

  10. Chang JR, Ho TH, Cheng CH, Chen AP (2006) Dynamic fuzzy OWA model for group multiple criteria decision. Soft Comput 10:543–554

    Article  Google Scholar 

  11. Cheng CH, Wei LY, Liu JW, Chen TL (2013) OWA-based ANFIS model for TAIEX forecasting. Econ Model 30:442–448

    Article  Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

  13. Fullér R, Majlender P (2003) On obtaining minimal variability OWA operator weights. Fuzzy Sets Syst 136:203–215

    Article  MathSciNet  MATH  Google Scholar 

  14. Gao J, Li M, Liu H (2015) Generalized ordered weighted utility averaging-hyperbolic absolute risk aversion operators and their applications to group decision-making. Eur J Oper Res 243:258–270

    Article  MathSciNet  MATH  Google Scholar 

  15. Gong Y (2011) A combination approach for obtaining the minimize disparity OWA operator weights. Fuzzy Optim and Decis Mak 10:311–321

    Article  MathSciNet  MATH  Google Scholar 

  16. Gong Y, Dai L, Hu N (2016) An extended minimax absolute and relative disparity approach to obtain the OWA operator weights. J Intell Fuzzy Syst 31:1921–1927

    Article  Google Scholar 

  17. Hong DH (2011) On proving the extended minimax disparity OWA problem. Fuzzy Sets Syst 168:35–46

    Article  MathSciNet  MATH  Google Scholar 

  18. Kaur Gurbinder, Dhar Joydip, Guha RK (2016) Minimal variability OWA operator combining ANFIS and fuzzy c-means for forecasting BSE index. Math Comput Simul 122:69–80

    Article  MathSciNet  Google Scholar 

  19. Kim Z, Singh VP (2014) Assessment of environmental flow requirements by entropy-based multi-criteria decision. Water Resour Manage 28:459–474

    Article  Google Scholar 

  20. Kishor A, Singh A, Pal N (2014) Orness measure of OWA operators: a new approach. IEEE Trans Fuzzy Syst 22:1039–1045

    Article  Google Scholar 

  21. Liu X, Chen L (2004) On the properties of parametric geometric OWA operator. Int J Approx Reason 35:163–178

    Article  MathSciNet  MATH  Google Scholar 

  22. Liu X (2005) On the properties of equidifferent RIM quantifier with generating function. Int J Gener Syst 34:579–594

    Article  MathSciNet  MATH  Google Scholar 

  23. Liu X (2007) The solution equivalence of minimax disparity and minimum variance problems for OWA operators. Int J Approx Reason 45:68–81

    Article  MathSciNet  MATH  Google Scholar 

  24. Liu X (2008) A general model of parameterized OWA aggregation with given orness level. Int J Approx Reason 48:598–627

    Article  MathSciNet  MATH  Google Scholar 

  25. Liu X, Han S (2008) Orness and parameterized RIM quantier aggregation with OWA operators: a summary. Int J Approx Reason 48:77–97

    Article  MATH  Google Scholar 

  26. Liu X (2009) On the methods of OWA operator determination with different dimensional instantiations. In: Proceedings of the 6th international conference on fuzzy systems and knowledge discovery, FSKD 2009, 14–16 Aug 2009, Tianjin, China, vol 7, pp 200–204. ISBN 978-076953735-1, Article number 5359982

    Google Scholar 

  27. Liu X (2011) A review of the OWA determination methods: classification and some extensions. In: Yager RR, 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, pp 49–90. ISBN 978-3-642-17909-9

    Google Scholar 

  28. Liu X (2012) Models to determine parameterized ordered weighted averaging operators using optimization criteria. Inf Sci 190:27–55

    Article  MathSciNet  MATH  Google Scholar 

  29. Liu HC, Mao LX, Zhang ZY, Li P (2013) Induced aggregation operators in the VIKOR method and its application in material selection. Appl Math Model 37:6325–6338

    Article  MathSciNet  Google Scholar 

  30. Llamazares B (2007) Choosing OWA operator weights in the field of social choice. Inf Sci 177:4745–4756

    Article  MathSciNet  MATH  Google Scholar 

  31. Luukka P, Kurama O (2013) Similarity classifier with ordered weighted averaging operators. Expert Syst Appl 40:995–1002

    Article  Google Scholar 

  32. Majlender P (2005) OWA operators with maximal Renyi entropy. Fuzzy Sets Syst 155:340–360

    Article  MathSciNet  MATH  Google Scholar 

  33. Mohammed EA, Naugler CT, Far BH (2016) Breast tumor classification using a new OWA operator. Expert Syst Appl 61:302–313

    Article  Google Scholar 

  34. O’Hagan M (1988) Aggregating template or rule antecedents in real-time expert systems with fuzzy set logic. In: Proceedings of 22nd annual IEEE Asilomar conference signals, systems, computers, Pacific Grove, CA, pp 681-689

    Google Scholar 

  35. Reimann O, Schumacher C, Vetschera R (2017) How well does the OWA operator represent real preferences? Eur J Oper Res 258:993–1003

    Article  MathSciNet  Google Scholar 

  36. Sang X, Liu X (2014) An analytic approach to obtain the least square deviation OWA operator weights. Fuzzy Sets Syst 240:103–116

    Article  MathSciNet  MATH  Google Scholar 

  37. Troiano L, Yager RR (2005) A measure of dispersion for OWA operators. In: Liu Y, Chen G, Ying M (eds) Proceedings of the eleventh international fuzzy systems association world congress, 28–31 July 2005, Beijing, China. Tsinghua University Press and Springer, pp 82–87

    Google Scholar 

  38. Vergara VM, Xia S (2010) Minimization of uncertainty for ordered weighted average. Int J Intell Syst 25:581–595

    Google Scholar 

  39. Wang Y-M, Parkan C (2005) A minimax disparity approach for obtaining OWA operator weights. Inf Sci 75:20–29

    Article  MathSciNet  MATH  Google Scholar 

  40. Wang JW, Chang JR, Cheng CH (2006) Flexible fuzzy OWA querying method for hemodialysis database. Soft Comput 10:1031–1042

    Article  Google Scholar 

  41. Wang YM, Luo Y, Liu XW (2007) Two new models for determining OWA operator weights. Comput Ind Eng 52:203–209

    Article  Google Scholar 

  42. Wu J, Sun B-L, Liang C-Y, Yang S-L (2016) A linear programming model for determining ordered weighted averaging operator weights with maximal Yager’s entropy. Comput Ind Eng 57(3):742–747

    Google Scholar 

  43. Xu ZS (2006) Dependent OWA operators. Lect Notes Comput Sci 3885:172–178

    Article  MATH  Google Scholar 

  44. Yager RR (1988) Ordered weighted averaging aggregation operators in multi-criteria decision making. IEEE Trans Syst Man Cybern 18:183-190

    Google Scholar 

  45. Yager RR (1993) Families of OWA operators. Fuzzy Sets Syst 59:125–148

    Article  MathSciNet  MATH  Google Scholar 

  46. Yager RR (1995) Measures of entropy and fuzziness related to aggregation operators. Inf Sci 82:147–166

    Article  MathSciNet  MATH  Google Scholar 

  47. Yager RR (1996) Constrained OWA aggregation. Fuzzy Sets Syst 81:89–101

    Article  MathSciNet  Google Scholar 

  48. Yager RR (1995) On the inclusion of variance in decision making under uncertainty. Int J Uncertain Fuzziness Knowl-Based Syst 4:401–419

    Article  MathSciNet  MATH  Google Scholar 

  49. Yager RR, Kacprzyk J (1997) The ordered weighted averaging operators: theory and applications. Kluwer, Norwell

    Book  MATH  Google Scholar 

  50. Yager RR, Filev D (1999) Induced ordered weighted averaging operators. IEEE Trans Syst Man Cybern—Part B: Cybern 29:141–150

    Article  Google Scholar 

  51. Yager RR (2007) Using stress functions to obtain OWA operators. IEEE Trans Fuzzy Syst 15:1122–1129

    Article  Google Scholar 

  52. Yager RR (2010) Including a diversity criterion in decision making. Int J Intell Syst 25:958–969

    MATH  Google Scholar 

  53. Yari G, Chaji AR (2012) Maximum Bayesian entropy method for determining ordered weighted averaging operator weights. Comput Ind Eng 63:338–342

    Article  Google Scholar 

  54. Zadrozny S, Kacprzyk J (2006) On tuning OWA operators in a flexible querying interface. Lect Notes Comput Sci 4027:97–108

    Article  Google Scholar 

  55. Zhou L, Chen H, Liu J (2012) Generalized logarithmic proportional averaging operators and their applications to group decision making. Knowl-Based Syst 36:268–279

    Article  Google Scholar 

  56. Zhou L, Chen H, Liu J (2012) Generalized weighted exponential proportional aggregation operators and their applications to group decision making. Appl Math Model 36:4365–4384

    Article  MathSciNet  MATH  Google Scholar 

  57. Zhou L, Tao Z, Chen H, Liu J (2015) Generalized ordered weighted logarithmic harmonic averaging operators and their applications to group decision making. Soft Comput 19:715–730

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Robert Fullér .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this chapter

Cite this chapter

Carlsson, C., Fullér, R. (2018). Maximal Entropy and Minimal Variability OWA Operator Weights: A Short Survey of Recent Developments. In: Collan, M., Kacprzyk, J. (eds) Soft Computing Applications for Group Decision-making and Consensus Modeling. Studies in Fuzziness and Soft Computing, vol 357. Springer, Cham. https://doi.org/10.1007/978-3-319-60207-3_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-60207-3_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60206-6

  • Online ISBN: 978-3-319-60207-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics