Ranking fuzzy numbers with integral value
Fuzzy Sets and Systems
Ranking fuzzy numbers by preference ratio
Fuzzy Sets and Systems
Performance measurement of supply chain management: A balanced scorecard approach
Computers and Industrial Engineering
Partner Selection and Evaluation in Virtual Research Center Based on Trapezoidal Fuzzy AHP
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II
Expert Systems with Applications: An International Journal
A fuzzy supplier selection model with the consideration of benefits, opportunities, costs and risks
Expert Systems with Applications: An International Journal
Evaluation of factors influencing knowledge sharing based on a fuzzy AHP approach
Journal of Information Science
Analytic network process and multi-period goal programming integration in purchasing decisions
Computers and Industrial Engineering
Fuzzy comprehensive evaluation of e-commerce and process improvement
WINE'05 Proceedings of the First international conference on Internet and Network Economics
Using ANP priorities with goal programming in resource allocation in transportation
Mathematical and Computer Modelling: An International Journal
Expert Systems with Applications: An International Journal
Close-loop or open hierarchical structures in green supply chain management under uncertainty
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
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.