Abstract
Abstract
In this paper, we investigate the multiple attribute decision making with interval-valued intuitionistic fuzzy numbers. Motivated by the ideal of dependent aggregation, we develop the dependent interval-valued intuitionistic fuzzy Einstein ordered weighted average (DIVIFEOWA) operator, in which the associated weights only depend on the aggregated interval-valued intuitionistic fuzzy arguments and can relieve the influence of unfair hesitant fuzzy arguments on the aggregated results by assigning low weights to those “false” and “biased” ones and then apply them to develop some approaches for multiple attribute decision making with interval-valued intuitionistic fuzzy numbers. Finally, an illustrative example for evaluating the computer network security is given to verify the developed approach and to demonstrate its practicality and effectiveness.
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