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- Simulating new multicriteria data from a given data set

Auteur(s): Rolland A.(Corresp.), Cugliari J.

Conference: DA2PL 2016 (Paderborn, DE, 2016-11-07)
Actes de conférence: , vol. p. ()


Résumé:

Several methods have been proposed in the past decades to deal with Multicriteria Decision Aiding (MCDA) problems. Even if the axiomatic foundations of these methods are generally wellknown, comparing the different methods or simply analysing the results produced by the methods on real-life problems is arduous as there is a lack of benchmark MCDA datasets in the literature. A solution is therefore to simulate new MCDA dataset examples. But the analysis of real-world examples show that one must deal with data that are lightly linked, and then it is important to take into account dependency between variables when simulating new datasets. We propose in this paper three different approaches to simulate new data based on existing small datasets. We describe these methods, we propose a quality analysis of the results, and we experiment the methods on different examples from the literature.