RT Conference Proceedings
T1 Introducing Uncertainty-Based Dynamics in MADM Environments
A1 Debora Di Caprio, 
A1 Santos Arteaga, Francisco Javier
AB . One of the main problems faced by the literature on Multi-AttributeDecision-Making (MADM) methods, which constitutes an inherent assumptionthat remains undiscussed through the different publications, is the fact that rankings are definitive. As a result, these models do not account for any of the consequences derived from the uncertainty inherent to the evaluations or the potentiallystrategic reports delivered by the experts. That is, once the ranking is computed,the decision makers (DMs) should select the first alternative, concluding the applicability and contribution of the corresponding model. There are no potential regretor uncertainty interactions triggered by the quality of the reports or their credibility. However, the results of the ranking are not always those preferred by theDMs, who may have to proceed through several alternatives, particularly if theevaluations provided by the experts fail to convey the actual value of the corresponding characteristics. This problem has not been considered in the MADMliterature, which has incorporated fuzziness and imprecision to its models, butnot accounted for the consequences of credibility in terms of regrettable choicesand the combinatorial framework that arises as soon as this possibility is incorporated into the analysis. We define a MADM setting designed to demonstratethe ranking differences arising as DMs incorporate the potential realizations froman uncertain evaluation environment in their choices. We illustrate the substantialranking modifications triggered by the subsequent dynamic and regret considerations while introducing important potential extensions within standard MADMtechniques.
SN 9783031252518
SN 9783031252525
SN 2367-3370
SN 2367-3389
YR 2023
FD 2023-03-01
LK https://hdl.handle.net/20.500.14352/113956
UL https://hdl.handle.net/20.500.14352/113956
LA eng
NO Di Caprio, D., Santos Arteaga, F.J. (2023). Introducing Uncertainty-Based Dynamics in MADM Environments. In: Aliev, R.A., Kacprzyk, J., Pedrycz, W., Jamshidi, M., Babanli, M.B., Sadikoglu, F. (eds) 15th International Conference on Applications of Fuzzy Systems, Soft Computing and Artificial Intelligence Tools – ICAFS-2022. ICAFS 2022. Lecture Notes in Networks and Systems, vol 610. Springer, Cham. https://doi.org/10.1007/978-3-031-25252-5_21
DS Docta Complutense
RD 7 abr 2025