Research on cloud-CRITIC-PDR method for hybrid multi-criteria decision making

Abstract

In order to solve the problems of insufficient uncertainty information measure, inaccuracy of weight calculation and incommensurability of indices in hybrid multi-criteria decision making, this paper introduces the Cloud-CRITIC weight calculation method and Cloud-CRITIC-PDR method, which combine cloud model, CRITIC method and Probabilistic Dominance Relation (PDR). In these two methods, the cloud model is used to characterize uncertainty, the Comprehensive information of CRITIC method has been modified in order to adapt to uncertain situation, the PDR method is used to compare schemes. A case study concerning supplier evaluation is given to demonstrate the merits of the cloud-CRITIC and cloud-CRITIC-PDR. The effectiveness and superiority of the developed methods are further illustrated through method comparison and sensitivity analysis. These combined methods can be used for dealing with decision-making problems with complex index types and strong data uncertainty, such as supplier evaluation and risk assessment. There are few papers about combining the cloud model, CRITIC method, and PDR method under hybrid indices decision-making situation at present, so this paper can provide a new perspective on hybrid MCDM.