异质环境下基于最小冒犯准则的分类共识决策方法研究

The classification-based consensus model with minimum violations in heterogeneous group decision making

本文从最小信息冒犯的视角研究异质环境下的分类决策问题.首先,提出方案分类与异质偏好之间的信息冒犯测量方法以及分类共识测量方法.接着,构建基于最小信息冒犯准则的异质分类共识决策模型,该模型能够在获取群体共识的方案分类的同时最小化群体信息冒犯水平.进一步,设计交互式的异质分类共识过程来引导决策个体调整偏好信息.最后,分析异质分类共识决策模型的理论性质,并使用一个算例来示范模型的运算过程.

This paper investigates the classification-based group decision making problem with heterogeneous preference information from a perspective of minimum information violations.Firstly,an approach for measuring information violations between alternatives classification and heterogeneous preference information,and a classification-based consensus measure method are proposed.Then,a classification-based consensus model with minimum information violations is developed to generate consensual alternative classifications under a heterogeneous preference context.Further,an interactive classification-based consensus reaching process with heterogeneous preference information is designed to guide decision makers to adjust their heterogeneous preference information.Moreover,the properties of proposed classification-based consensus reaching model are discussed.Finally,a numerical example is offered to demonstrate the application process of the proposal.