Fuzzy Multicriteria Decision Making Model for HPP Alternative Selection

  • Zedina LavićEmail author
  • Sabina Dacić-Lepara
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 59)


In decision making models developed using the Analytic Hierarchy Process, expert judgments expressed verbally are quantified using the Saaty’s scale in the way that they were assigned strict values (crisp numbers). As expert judgments are not really strict, there is a need for these judgments to be more properly quantified. Instead of strict values, they need to be assigned fuzzy numbers. In this paper a fuzzy model for multicriteria decision making on the selection of the best alternative from the Pareto set of technical solutions for the hydroelectric power plant is developed using a Fuzzy Analytic Hierarchy Process. The model is tested on a concrete example and the results are compared with the results of a model developed using the classic Analytic Hierarchy Process.


Sustainable development Hydropower plant Multicriteria decision making Fuzzy analytic hierarchy process Economic Technical Social and environmental criteria 


  1. 1.
    Saaty, T.L.: Analytic Hierarchy Process. McGraw-Hill, New York (1980)zbMATHGoogle Scholar
  2. 2.
    Zadeh, L.A.: Fuzzy set. Inf. Control 8, 338–353 (1965)CrossRefGoogle Scholar
  3. 3.
    Lavic, Z., Dacić-Lepara, S.: Multicriteria decision making model for HPP alternative selection. In: Hadžikadić, M., Avdaković, S. (eds.) Advanced Technologies, Systems, and Applications II. AG 2018. Lecture Notes in Networks and Systems, vol. 28, pp 170–177. Springer, Heidelberg (2018)
  4. 4.
    Kahraman, C.: Fuzzy Multi-criteria Decision Making Theory and Applications with Recent Developments. Springer, New York (2008)CrossRefGoogle Scholar
  5. 5.
    Kabir, G., Akhtar, H.A.: Comparative analysis of AHP and fuzzy AHP models for multicriteria inventory classification. Int. J. Fuzzy Log. Syst. (IJFLS) 1(1), 1–16 (2011)Google Scholar
  6. 6.
    Chang, D.Y.: Applications of the extent analysis method on fuzzy AHP. Eur. J. Oper. Res. 95(1996), 649–655 (1996)CrossRefGoogle Scholar
  7. 7.
    Zyoud, S., Kaufmann, L., Shaheen, H., Samhan, S., Fuchs-Hanusch, D.: A framework for water loss management in developing countries under fuzzy environment: integration of fuzzy AHP with fuzzy TOPSIS. Expert Syst. Appl. 61, 86–105 (2016)CrossRefGoogle Scholar
  8. 8.
    Bozbura, F.T., Beskese, A., Kahraman, C.: Prioritization of human capital measurement indicators using fuzzy AHP. Expert Syst. Appl. 32(4), 1100–1112 (2007). Scholar
  9. 9.
    Chen, J., Hsieh, H., Do, Q.: Evaluating teaching performance based on fuzzy AHP and comprehensive evaluation approach. Appl. Soft Comput. 28, 100–108 (2015)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Capital InvestmentsEPC Elektroprivreda B&H D.D. SarajevoSarajevoBosnia and Herzegovina

Personalised recommendations