Abstract
In an uncertain environment, the process of fuzzy cross-evaluation in data envelopment analysis (DEA) models is explained by different types of fuzzy data. In this paper, the fuzzy cross-efficiency matrix with different types of fuzzy data will be changed into a cross-evaluation similarity matrix by similarity theory of generalized trapezoidal fuzzy numbers. Based on the fuzzy information retrieval (FIR) method, a new ordered-geometric-mean averaging operator is defined to yield aggregation weights by the relevance between the self-evaluation and cross-evaluation of each decision-making unit (DMU). Furthermore, the common neighbor DMU selection algorithm is constructed to classify the DMUs. Then, the fuzzy logic rules are proposed to modify the aggregation results by combining the clustering results. Finally, this paper demonstrates the applicability of fuzzy cross-efficiency aggregation using the FIR method by taking an example of 12 suppliers from the semiconductor industry.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
