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Dual hesitant fuzzy aggregation operators based on Bonferroni means and their applications to multiple attribute decision making

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In this paper, we investigate the multiple attribute decision making problems with dual hesitant fuzzy information. Motivated by the idea of Bonferroni mean and Choquet integral, we develop the aggregation techniques called the dual hesitant fuzzy choquet ordered Bonferroni mean operator for aggregating the dual hesitant fuzzy information. We research its properties and discuss its special cases. We also apply the newly defined operator to deal with multiple attribute decision making problems under dual hesitant fuzzy environment. Finally, an illustrative example is given to show the developed method and demonstrate its practicality and effectiveness.

Abstract

In this paper, we investigate the multiple attribute decision making problems with dual hesitant fuzzy information. Motivated by the idea of Bonferroni mean and Choquet integral, we develop the aggregation techniques called the dual hesitant fuzzy choquet ordered Bonferroni mean operator for aggregating the dual hesitant fuzzy information. We research its properties and discuss its special cases. We also apply the newly defined operator to deal with multiple attribute decision making problems under dual hesitant fuzzy environment. Finally, an illustrative example is given to show the developed method and demonstrate its practicality and effectiveness.

참고문헌 (36)

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