基于信息取样偏差快速自修正Delphi方法的群体多属性决策

针对传统群体多属性决策过程偏向信息描述而忽视对决策过程本身的改善,Delphi方法过程繁琐、响应滞后、受群体心理因素影响的缺陷,提出一种解决群体多属性决策问题的新模型,即将信息取样偏差模型获取决策综合满意度的技术原理引入到Delphi方法中,得到一个具备快速自修正能力的Delphi群体多属性决策模型,并将模型应用到高校学生选课的问题中加以验证.结果表明,新模型无需在决策值与决策权重间进行复杂的权衡,并使得Delphi过程能快速收敛.

Multi-attribute Group Decision-making Based on Rapid Self-adjusting Delphi Method with Biased Information Sampling

A multi-attribute group decision-making model(MAGDMM) based on a rapid self-adjusting method is presented to solve problems that take place in the procedure of conventional Delphi decision making model,such as a complicated and cumbersome processing procedure with a notable outcome lag,biased decision results caused by group psychological factors,etc.This model introduces the comprehensive satisfaction evaluation technology,developed according to biased information sampling model,into the Delphi method to improve its rapid processing and self-adjusting abilities.Moreover,as an illustrative example,the curricula-variable problem in colleges is solved by using this new model.Results show that there are no complex trade-offs when judging decision values and weights,and it significantly improves the performance of convergency.