@article {IOPORT.05268565,
    author       = {Renaud, Jean and Levrat, Eric and Fonteix, Christian},
    title        = {Weights determination of OWA operators by parametric identification.},
    year         = {2008},
    journal      = {Mathematics and Computers in Simulation},
    volume       = {77},
    number       = {5-6},
    issn         = {0378-4754},
    pages        = {499-511},
    publisher    = {Elsevier Science B.V. (North-Holland), Amsterdam},
    doi          = {10.1016/j.matcom.2007.11.024},
    abstract     = {Summary: This contribution presents a new approach on weights determination in industrial decision making aided by Ordered Weighted Average (OWA) operators. Multi-criteria decision aid is a good way, for an industrialists, to determine his preferred compromise products, in the case of risk products or innovative products. The multi-criteria decision support chosen is the OWA operators, introduced by {\it R. R. Yager} [IEEE Trans. Syst. Man Cybern. 18, No.~1, 183--190 (1988; Zbl 0637.90057)]. The interest of this aggregation method is, beyond its simplicity of use, product evaluation according to a unique scale. Furthermore, the weights are not fixed by criterion but according to the utility level. First, a learning sample is ranked by the decision-maker. Then, this ranked sample is used in order to determine the weights by parametric identification. For this, an hypothesis of equipartition of the scores of each sample is used. An industrial application, from food production, illustrates this approach. The ranks obtained from several samples are compared.},
    identifier   = {05268565},
}