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Multicriteria estimation of probabilities on basis of expert non-numeric, non-exact and non-complete knowledge

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  • Hovanov, Nikolai
  • Yudaeva, Maria
  • Hovanov, Kirill

Abstract

A new method of alternatives' probabilities estimation under deficiency of expert numeric information (obtained from different sources) is proposed. The method is based on the Bayesian model of uncertainty randomization. Additional non-numeric, non-exact, and non-complete expert knowledge (NNN-knowledge, NNN-information) is used for final estimation of the alternatives' probabilities. An illustrative example demonstrates the proposed method application to forecasting of oil shares price with the use of NNN-information obtained from different experts (investment firms).

Suggested Citation

  • Hovanov, Nikolai & Yudaeva, Maria & Hovanov, Kirill, 2009. "Multicriteria estimation of probabilities on basis of expert non-numeric, non-exact and non-complete knowledge," European Journal of Operational Research, Elsevier, vol. 195(3), pages 857-863, June.
    • Handle: RePEc:eee:ejores:v:195:y:2009:i:3:p:857-863
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    3. Martin Boďa & David Cole & Mária Murray Svidroňová & Jolana Gubalová, 2022. "Prevailing narratives versus reality of a small and medium town decline in a CEE country," Operational Research, Springer, vol. 22(3), pages 3113-3145, July.
    4. Shmelev, Stanislav E. & van den Bergh, Jeroen C.J.M., 2016. "Optimal diversity of renewable energy alternatives under multiple criteria: An application to the UK," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 679-691.

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