COPPE-Cosenza Fuzzy Hierarchy Model

The program implements the COPPE-Cosenza Fuzzy Hierarchy Model. The model was based on the evaluation of local alternatives, representing regional potentialities, so as to fulfill demands of economic projects. After defining demand profiles in terms of their technological coefficients, the degree of importance of factors is defined so as to represent the productive activity. The method can detect a surplus of supply without the restriction of the distance of classical algebra, defining a hierarchy of location alternatives. In COPPE-Cosenza Model, the distance between factors is measured in terms of the difference between grades of memberships of the same factors belonging to two or more sets under comparison. The required factors are classified under the following linguistic variables: Critical (CR); Conditioning (C); Little Conditioning (LC); and Irrelevant (I). And the alternatives can assume the following linguistic variables: Excellent (Ex), Good (G), Regular (R), Weak (W), Empty (Em), Zero (Z) and Inexistent (In). The model also provides flexibility, allowing different aggregation rules to be performed and defined by the Decision Maker. Such feature is considered in this package, allowing the user to define other aggregation matrices, since it considers the same linguistic variables mentioned.


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0.1.3 by Pier Taranti, 3 years ago

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Authors: Pier Taranti [aut, cre] , Leonardo Pessoa [aut] , Carlos Cosenza [aut]

Documentation:   PDF Manual  

GPL-2 | file LICENSE license

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