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针对多粒度语言判断矩阵的群决策问题提出基于相对熵的最优化模型的排序方法。在多粒度语言偏好信息的导出函数基础上定义了语言判断矩阵对应的导出模糊互补判断矩阵,并给出其排序向量的计算式;同时采用语言判断矩阵的一致性指标来确定专家重要性程度的权向量;在相对熵的意义下构建了群决策排序向量的最优化模型,探讨了模型的求解方法。实例分析表明该模型是可行和有效的。
Aiming at the problem of group decision making in multi-granularity language judgment matrix, a ranking method of optimization model based on relative entropy is proposed. Based on the derivation function of multi-granularity language preference information, the derivation fuzzy complementary judgment matrix corresponding to the language judgment matrix is defined and the calculation formula of the ranking vector is given. Meanwhile, the consistency index of the language judgment matrix is used to determine the degree of the importance of the experts In the sense of relative entropy, an optimization model of group decision ordering vector is constructed and the solution method of the model is discussed. The case study shows that the model is feasible and effective.