show,Aggregation.matrix-method

show

show,Aggregation.matrix.default-method

show,Aggregation.matrix.membership.difference-method

show,Factor-method

show,Factors.of.interest-method

show,Option.factor.availability-method

show,Option.resources-method

show,Option-method

show,Option.portfolio-method

show,Project.criterion-method

show,Project.criteria-method

show,Project-method

show,Project.portfolio-method

show,Coppe.cosenza-method

object

Aggregation.matrix.default

<p>Aggregation.matrix.membership.difference</p>

Aggregation.matrix.membership.difference

Factor

Factors.of.interest

Option.factor.availability

Option.resources

Option

Option.portfolio

Project.criterion

Project.criteria

Project

Project.portfolio

Coppe.cosenza

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.

show,Aggregation.matrix-method: show

Description

Usage

Arguments