A Geometric Fuzzy-Based Approach for Airport Clustering

Airport classification is a common need in the air transport field due to several purposes--such as resource allocation, identification of crucial nodes, and real-time identification of substitute nodes--which also depend on the involved actors' expectations. In this paper a fuzzy-based procedure has been proposed to cluster airports by using a fuzzy geometric point of view according to the concept of unit-hypercube. By representing each airport as a point in the given reference metric space, the geometric distance among airports--which corresponds to a measure of similarity--has in fact an intrinsic fuzzy nature due to the airport specific characteristics. The proposed procedure has been applied to a test case concerning the Italian airport network and the obtained results are in line with expectations.

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