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Moreover, while crisp input and output data are indispensable in traditional DEA, real-world production processes may involve imprecise or ambiguous input and output data. Fuzzy set theory has been widely used to formalize and represent the impreciseness and ambiguity inherent in human decision-making. In this paper, we propose a new fuzzy DEA method for clustering operating units in a fuzzy environment by considering the priority between the clusters and the priority between the operating units in each cluster simultaneously. A numerical example and a case study for the Jet Ski purchasing decision by the Florida Border Patrol are presented to illustrate the efficacy and the applicability of the proposed method. <\/jats:p>","DOI":"10.1142\/s0218488513500037","type":"journal-article","created":{"date-parts":[[2013,3,1]],"date-time":"2013-03-01T18:16:15Z","timestamp":1362161775000},"page":"29-54","source":"Crossref","is-referenced-by-count":16,"title":["A FUZZY DATA ENVELOPMENT ANALYSIS FOR CLUSTERING OPERATING UNITS WITH IMPRECISE DATA"],"prefix":"10.1142","volume":"21","author":[{"given":"SABER","family":"SAATI","sequence":"first","affiliation":[{"name":"Department of Mathematics, Tehran-North Branch, Islamic Azad University P.O. 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