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Consensus measures based on a fuzzy concept

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  • Dombi, József
  • Jónás, Tamás

Abstract

When evaluations concerning a decision alternative are available from multiple sources (e.g. criteria or experts), the individual evaluation inputs are typically combined into one value that may be viewed as an aggregate evaluation of the alternative. In such situations, besides the aggregate value, the extent to which the inputs agree is also an important piece of information. Consensus measures are utilized for measuring this degree of agreement. In our study, we will introduce the so-called decumulative distribution function of the individual inputs measured on the unit interval. Using a fuzziness measure of this function, we will construct a consensus measure that satisfies seven reasonable properties. In the proposed construction, a consensus measure depends on a fuzzy entropy that may be viewed as the generator of the proposed consensus measure. This generator function-based nature of the proposed consensus measure makes it flexible. Also, we will prove that in a special case, the new consensus measure coincides with the measure of Bonferroni consensus with implication pairs. Furthermore, we will describe how our proposal can be extended to a weighted version.

Suggested Citation

  • Dombi, József & Jónás, Tamás, 2024. "Consensus measures based on a fuzzy concept," European Journal of Operational Research, Elsevier, vol. 315(2), pages 642-653.
    • Handle: RePEc:eee:ejores:v:315:y:2024:i:2:p:642-653
    DOI: 10.1016/j.ejor.2024.01.004
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