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Research on objective index weight configuration in the field of multiple attribute decision making is conducted in this paper. Evaluating objects are divided into different grey categories according to essential natural characteristics by grey correlation clustering method. Maximum entropy configuration model of objective index weight is built based on the similarity of natural characteristics difference in the same grey category and the diversity of natural characteristics difference of the different grey categories. In case study, comparative analysis with other methods is conducted. The results demonstrate that the model in this paper is feasible and effective. So, a new solution to objective index weight configuration in the field of multiple attribute decision making is put forward. [ABSTRACT FROM AUTHOR]

The problem of seeking weights of decision-makers and attributes is studied in multi-attribute group decision making with interval grey numbers. For avoiding conflict between subjective weights and objective ones computed from attributes' values given by decision makers, the comprehensive weights are calculated by combining subjective weights and objective ones, where objective weights of attributes are obtained by using the maximum entropy model under the constrains of grey relation degree between the optimal project and every one. While, based on the degree of group consensus and information distribution, the weights of decision-makers are obtained by the maximum entropy thought and grey relation degree between every decision maker's comprehensive evaluations and average group evaluations. Finally, an aggregation approach of group decision making with interval grey numbers is presented. The numerical example is proved to verify the proposed method is more reasonable than other methods. [ABSTRACT FROM AUTHOR]