Some Construction Methods for Pseudo-Overlaps and Pseudo-Groupings and Their Application in Group Decision Making

Author:

García-Zamora Diego1ORCID,Paiva Rui2ORCID,Cruz Anderson34ORCID,Fernandez Javier5ORCID,Bustince Humberto5ORCID

Affiliation:

1. Department of Computer Sciences, University of Jaen, 23071 Jaén, Spain

2. Instituto Federal de Educação, Ciência e Tecnologia do Ceará, Fortaleza 61939-140, Brazil

3. Metrópole Digital Institute, Federal University of Rio Grande do Norte, Natal 59078-900, Brazil

4. Navarra Artificial Intelligence Research Center, 310006 Pamplona, Spain

5. Department of Statistics, Computer Sciences and Mathematics, Public University of Navarra, 31009 Pamplona, Spain

Abstract

In many real-world scenarios, the importance of different factors may vary, making commutativity an unreasonable assumption for aggregation functions, such as overlaps or groupings. To address this issue, researchers have introduced pseudo-overlaps and pseudo-groupings as their corresponding non-commutative generalizations. In this paper, we explore various construction methods for obtaining pseudo-overlaps and pseudo-groupings using overlaps, groupings, fuzzy negations, convex sums, and Riemannian integration. We then show the applicability of these construction methods in a multi-criteria group decision-making problem, where the importance of both the considered criteria and the experts vary. Our results highlight the usefulness of pseudo-overlaps and pseudo-groupings as a non-commutative alternative to overlaps and groupings.

Funder

Spanish Ministry of Universities

Brazilian funding agency CNPq

Publisher

MDPI AG

Subject

Geometry and Topology,Logic,Mathematical Physics,Algebra and Number Theory,Analysis

Reference44 articles.

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3. Wieczynski, J., Lucca, G., Borges, E., and Dimuro, G. (December, January 28). Application of the Sugeno Integral in Fuzzy Rule-Based Classification. Proceedings of the Intelligent Systems, PT I, Campinas, Brazil.

4. Beliakov, G., Pradera, A., and Calvo, T. (2007). Aggregation Functions: A Guide for Practitioners; Studies in Fuzziness and Soft Computing, Springer.

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