A Large Group Decision Making Method Based on Public Evaluation

Abstract

Abstract:

Large group decision-making (LGDM) is a special group decision-making (GDM) issue, in which a large number of persons take part in the decision-making process. The objective of this paper is to develop a new method to address the LGDM issue which is based on the public evaluation. Firstly, we divide the large evaluation data into several groups according to decision makers' professions. Normal distribution and logarithmic normal distribution are used to fit each group of data and select the better one. Secondly, the decision weight of each group concerning each object is obtained by aggregating the subjective weight, which is provided by the data rate, and the objective weight is determined according to the level of consensus among participators' evaluations. Thirdly, according to the nature of normal distribution, the normal distributions are assembled to one. Finally, by calculating the dominances of any two objects, we get the dominance matrix for decide making based on PROMETHEEⅡ. The practicality and superiority of the suggested method is verified through case study.

Key words: multi-attribute decision-making, large group, normal distribution, logarithmic normal distribution, dominance degree

Ren Rongrong, Li Wenwen, Zhao Meng, Li Xiaoqi. A Large Group Decision Making Method Based on Public Evaluation[J]. , 2018, 30(10): 238-247.

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