Group Decision and Negotiation

, Volume 21, Issue 2, pp 153–183 | Cite as

Fuzzy Set Based Consensus Schemes for Multicriteria Group Decision making Applied to Strategic Planning

  • R. O. ParreirasEmail author
  • P. Ya. Ekel
  • D. C. Morais


This paper studies three consensus schemes based on fuzzy models for dealing with the input of multiple experts in multicriteria decision making. The consensus schemes are based on different aggregation procedures for constructing a collective decision. In the paper, we propose a methodology that makes use of the three consensus schemes implemented by a coordination mode that creates an efficient manner of exploiting the capabilities of each member of the group in a cooperative work. The applicability and efficiency of the proposed methodology is demonstrated through an application related to strategic planning.


Group decision Consensus Fuzzy preference relations Strategic planning 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Ackoff RL (1969) A concept of corporate planning. Wiley, New YorkGoogle Scholar
  2. Alonso S, Herrera-Viedma E, Cabrerizo FJ, Chiclana F, Herrera F (2007) Visualizing consensus in group decision making situations. In: Proceedings of the 2007 IEEE international conference on fuzzy systems. London, pp 1818–1823Google Scholar
  3. Bernardes P, Ekel P, Kotlarewski J, Parreiras R (2009) Fuzzy set based multicriteria decision making and its applications, in progress on nonlinear analysis. Nova Science Publisher, Hauppauge, pp 247–272Google Scholar
  4. Black JA, Boal KB (1994) Strategic resources: traits, configurations and paths to sustainable competitive advantage. Strateg Manag J 15: 131–148CrossRefGoogle Scholar
  5. De Baets P, Fodor JC (1997) Twenty years of fuzzy preference structures. Rivista di Matematica per le Scienze Economiche e Sociali 20: 45–66Google Scholar
  6. Ekel P, Parreiras R (2009) Procedures for group multicriteria decision making using fuzzy preference relation modeling. In: Proceedings of the XLI Brazilian symposium of operational research. Porto Seguro, pp 1789–1800 (in Portuguese)Google Scholar
  7. Ekel P, Pedrycz W, Schinzinger R (1998) A general approach to solving a wide class of fuzzy optimization problems. Fuzzy Sets Syst 97: 49–66CrossRefGoogle Scholar
  8. Ekel PYa, Schuffner Neto FH (2006) Algorithms of discrete optimization and their application to problems with fuzzy coefficients. Inf Sci 176: 2846–2868CrossRefGoogle Scholar
  9. Ekel PYa, Queiroz J, Parreiras R, Palhares R (2009) Fuzzy set based models and methods of multicriteria group decision making. Nonlinear Anal Theory Methods Appl 71: e409–e419CrossRefGoogle Scholar
  10. Fodor JC, Roubens M (1994) Fuzzy preference modelling and multicriteria decision support. Kluwer, BostonGoogle Scholar
  11. Forman E, Peniwati K (1998) Aggregating individual judgments and priorities with the Analytic Hierarchy Process. Eur J Oper Res 108: 165–169CrossRefGoogle Scholar
  12. García-Lapresta JL (2008) Favoring consensus and penalizing disagreement in group decision making. J Adv Comput Intell Intell Inform 12: 416–421Google Scholar
  13. Grabisch M, Orlovski SA, Yager RR (1998) Fuzzy aggregation of numerical preferences in Fuzzy Sets. In: Decision analysis, operations research and statistics, the handbook of fuzzy sets series, vol 4. Kluwer, Boston, pp 31–68Google Scholar
  14. Harrison EF (1995) Strategic planning maturities. Manag Decis J 33: 48–55CrossRefGoogle Scholar
  15. Herrera-Viedma E, Herrera F, Chiclana F (2002) A consensus model for multiperson decision making with different preference structures. IEEE Trans Syst Man Cybern Part A Syst Hum 32: 394–402CrossRefGoogle Scholar
  16. Herrera-Viedma E, Alonso S, Chiclana F, Herrera F (2007) A consensus model for group decision making with incomplete fuzzy preference relations. IEEE Trans Fuzzy Syst 15: 863–877CrossRefGoogle Scholar
  17. Hsu HM, Chen CT (1996) Aggregation of fuzzy opinions under group decision making. Fuzzy Sets Syst 79: 279–285CrossRefGoogle Scholar
  18. Kaplan RS, Norton D (1996) The balanced scorecard: translating strategy into action. Harvard Business School, BostonGoogle Scholar
  19. Kauffman A, Gupta MM (1985) Introduction to fuzzy arithmetic: theory and applications. Van Nostrand Reinhold, New YorkGoogle Scholar
  20. Li RJ (1999) Fuzzy method in group decision making. Comput Math Appl 38: 91–101CrossRefGoogle Scholar
  21. Lu C, Lan J, Wang Z (2006) Aggregation of fuzzy opinions under group decision-making based on similarity and distance. J Syst Sci Complex 19: 63–71CrossRefGoogle Scholar
  22. Lu J, Zhang G, Ruan D, Wu F (2007) Multi-objective group decision making: methods, software and applications with fuzzy set techniques. Imperial College Press, LondonGoogle Scholar
  23. Orlovski SA (1978) Decision making with a fuzzy preference relation. Fuzzy Sets Syst 1: 155–167CrossRefGoogle Scholar
  24. Orlovsky SA (1981) Problems of decision making with fuzzy information. Nauka, Moscow (in Russian)Google Scholar
  25. Parreiras R, Ekel P, Martini JSC, Palhares RM (2010) A flexible consensus scheme for multicriteria group decision making under linguistic assessments. Inf Sci 180: 1075–1089CrossRefGoogle Scholar
  26. Pedrycz W, Gomide F (1998) An introduction to fuzzy sets: analysis and design. MIT Press, CambridgeGoogle Scholar
  27. Pedrycz W, Ekel P, Parreiras R (2010) Fuzzy multicriteria decision-making: models, methods and applications. Wiley, ChichesterCrossRefGoogle Scholar
  28. Phillips LD, Phillips MC (1993) Facilitated work groups: theory and practice. J Oper Res Soc 44: 533–549Google Scholar
  29. Steiner GA (1979) Strategic planning. Free Press, New YorkGoogle Scholar
  30. Wang Y-M, Fan Z-P (2007) Fuzzy preference relations: aggregation and weight determination. Comput Ind Eng 53: 163–172CrossRefGoogle Scholar
  31. Wang Y-M, Parkan C (2008) Optimal aggregation of fuzzy preference relations with an application to broadband internet service selection. Eur J Oper Res 187: 1476–1486CrossRefGoogle Scholar
  32. Zimmermann HJ (1990) Fuzzy set theory and its application. Kluwer, BostonGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Post-Graduate Program in Electrical EngineeringPontifical Catholic University of Minas GeraisBelo HorizonteBrazil
  2. 2.Graduate Program in Electrical EngineeringPontifical Catholic University of Minas GeraisBelo HorizonteBrazil
  3. 3.Department of Production EngineeringFederal University of PernambucoRecifeBrazil

Personalised recommendations