DECISION COMPROMISE MODELLING BASED ON OWA OPERATORS

This paper is concerned by the industrial application of Ordered Weighted Averaging OWA operators, introduced by Yager. These operators allow to express the type of compromises, by the notion of linguistic quantifiers, such as “most” of criteria. The interest of this method of aggregation is, beyond its simplicity of use, its evaluation of products according a unique scale. Furthermore, the weights are not fixed by criteria but by levels of performance. In this paper we present a methodology of classification of products by two approaches. The first one is based on a learning sample and the second one on linguistic quantifiers. An industrial application, from a food production, illustrates these approaches. We then discuss the classifications obtained by these two approaches and we present a comparison.