A Method for Knowledge Checking Service Selection with Incomplete Weight Information Based on the Grey Related Analysis and Data Envelopment Analysis in Fuzzy Environment

摘要

The knowledge checking service (KCS) is critical for safeguarding the quality of knowledge. In organizations, there are many knowledge checking services with similar functions but different qualities, in order to select the best KCS, the method which combines grey related analysis (GRA) with data envelope analyzes (DEA) with incomplete weight information in fuzzy environment is proposed. In the method, the evaluation information is given linguistically and processed by the 2-tuple linguistic model and GRA. The DEA model is constructed to derive the precise weight information. Afterwards, by solving DEA model, the order of the alternatives can be derived. In the method, the combination of the advantages of DEA and grey correlation analysis leads to the avoidance of subjectivity and make the selection more accurately. The applicability of the proposed method is validated by an example.