An Ordered Weighted Averaging Operator Based on Extreme Values Reductions
- https://doi.org/10.2991/asum.k.210827.039How to use a DOI?
- Aggregation operator, Ordered Weighted Averaging operators, Extreme Values Reduction
Classical Group Decision Making (GDM) problems require the use of aggregation functions to fuse the information elicited from the experts who participate in the decision process. One of the most widely adopted aggregation functions employed in GDM are the Ordered Weighting Averaging (OWA) operators which use a linear linguistic quantifier to define the relevance of each expert. However, the use of linear quantifiers to fuse information presents some disadvantages due to the fact that they can assign the value 0 to the weights corresponding to the most extreme opinions, completely ignoring them. In this contribution, we propose a novel OWA operator which uses an Extreme Values Reduction (EVR) as linguistic quantifier to compute the relevance of each expert. The resulting operator, so-called, EVR-OWA operator, will always assign a non zero weight to every expert but giving greater importance to the intermediate opinions. After defining the EVR-OWA operator for a generic EVR, the EVR-OWA operators associated to two concrete families of EVRs are proposed and their main measures, i.e. mean, standard deviation, orness measure and entropy, computed. Finally an example of aggregation is developed to show the performance of the EVR-OWA operator.
- © 2021, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Diego García-Zamora AU - Álvaro Labella AU - Rosa M. Rodríguez AU - Luis Martínez PY - 2021 DA - 2021/08/30 TI - An Ordered Weighted Averaging Operator Based on Extreme Values Reductions BT - Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP) PB - Atlantis Press SP - 290 EP - 297 SN - 2589-6644 UR - https://doi.org/10.2991/asum.k.210827.039 DO - https://doi.org/10.2991/asum.k.210827.039 ID - García-Zamora2021 ER -