A TFN-ANP based approach to evaluate Virtual Research Center comprehensive performance
The performance evaluation of Virtual Research Center (VRC) is an intrinsically complex multi-dimensional process and it should be evaluated and compared in a multi-criteria analysis method. To solve the problems caused by the fuzzy decision making, quantifying the qualitative indexes and dealing with the interdependence and interaction of some indexes during the process of VRC performance evaluation, a comprehensive performance evaluation method based on triangular fuzzy number and analytic network process (TFN-ANP) is proposed. In the method, an index evaluation system is first established and the interactive relationships of the evaluation indexes are analyzed. Secondly, the index evaluation decision-making matrix is constructed and the indexes attribute values are fuzzed with triangular fuzzy numbers. Thirdly, the evaluative indexes weights are determined by analytic network process. Then the concrete solving process is derived and the fuzzy utility value weights are ranked by the priority method with decision maker risk preference. In the end, the four project teams of Yalong River VRC are taken as examples, then their comprehensive performances are evaluated by TFN-ANP model and the utility value priorities are ranked, which could provide decision supports for VRC to optimize operational performance. In addition, a comparison with the previous method is performed, and experimental results are encouraging, which fully demonstrates the effectiveness and superiority of the proposed approach. (C) 2010 Elsevier Ltd. All rights reserved.
performance evaluation virtual research center (vrc) utility value multiple-criteria decision-making (mcdm) analytic network process (anp) triangular fuzzy number (tfn)