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This paper studies the multi-attribute group decision-making problems with unknown experts’ weights under interval-valued intuitionistic fuzzy environment. First, in order to providemore flexibilities for decision-makers in actual decision-making problems, a novel cross-entropy measure with parameter of interval-valued intuitionistic fuzzy set (IVIFS) based on J-divergence is proposed. The novel cross-entropy measure can obtain more flexible and practical optimal ranking results by adjusting the parameter. Then, by using the designed cross-entropy measure, two models are established to obtain experts’ weights, which consider the influence of experts’ experience and professional knowledge on experts’ weights. Finally, two examples are provided to illustrate the effectiveness and applicability of optimizing the group decision-making approach.

the international journal of computational intelligence systems/international journal of computational intelligence systems

Novel Cross-Entropy Based on Multi-attribute Group Decision-Making with Unknown Experts' Weights Under Interval-Valued Intuitionistic Fuzzy Environment