Linguistic Multi-Expert Decision Making Involving Semantic Overlapping [chapter]

Hong-Bin Yan, Van-Nam Huynh, Yoshiteru Nakamori
2010 Advances in Intelligent and Soft Computing  
This paper presents a probabilistic model for linguistic multi-expert decision making (MEDM), which is able to deal with vague concepts in linguistic aggregation and decision-makers' preference information in choice function. In linguistic aggregation phase, the vagueness of each linguistic judgement is captured by a possibility distribution on a set of linguistic labels. A confidence parameter is also incorporated into the basic model to model experts' confidence degree. The basic idea of this
more » ... linguistic aggregation is to transform a possibility distribution into its associated probability distribution. The proposed linguistic aggregation results in a set of labels having a probability distribution. As a choice function, a target-oriented ranking method is proposed, which implies that the decision-maker is satisfactory to choose an alternative as the best if its performance is as at least "good" as his requirements.
doi:10.1007/978-3-642-11960-6_26 dblp:conf/ium/YanHN10 fatcat:3wetngt4s5cgxkayt5sfobt4ky