Abstract

The Bonferroni mean is an important aggregation technique which can reflect the correlations of the aggregation arguments. The classical Bonferroni mean is an extension of the arithmetic mean, and is generalized by some researchers based on the idea of the geometric mean. In this paper, based on the Bonferroni mean and the harmonic mean, we introduce some new aggregating operators: the fuzzy Bonferroni harmonic mean (FBHM) operator, the fuzzy ordered Bonferroni Harmonic Mean (FOBHM) operator, the fuzzy hybrid Bonferroni harmonic mean (FHBHM) operator and the fuzzy induced ordered Bonferroni harmonic mean (FIOBHM) operator. Finally, we develop an approach to multiple attribute decision making on the basis of the proposed aggregation techniques and an example is provided to illustrate our proposed method

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