Fuzzy Sets and Economics

Abstract

To classify objects is a common approach in most studies. Many classification methods exist in linear analysis. Each of this method, most particularly the clustering, has as its main objective, the creation of a partition on a set of objects. The principal problem that this approach presents is that of a standard choice of a proximity measure on a set. The choice of this standard is required at all levels of a classification work. When the objects to be classified have fuzzy outlines, the problem of choice and the definition of a “good” index appear. We have proposed a distance index based on a parametric family of fuzzy operators, which will be used in other to construct a fuzzy indicator and to classify not well-defined objects. This new indicator has been applied to measure the efficiency of a transport system for foodstuffs. The question here is to define and to try to explain the efficiency criteria using the transportation characteristics and its organization. These characteristics has previously been broken up by means of fuzzy uncoupling, the latter being a Zadeh’s linguistic connective.