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A TOPSIS–Based Cooperative Strategy for Solving Imprecise MCDM Problems

  • Universidad Distrital Francisco José de Caldas
  • Charles University

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

The imprecise TOPSIS method has attracted attention in the last years from different perspectives. Most of current methods are based on choosing a set of crisp scores such as midpoints, expected values, pessimistic/optimistic scores, etc. from a set of imprecise ones to then compute the TOPSIS method and select the best alternative. So, to deal with both homogeneous decisions/information we propose a cooperative strategy for integrating partial TOPSIS decisions into a context-based convex method to finally provide an aggregated decision. The proposed strategy is explained and applied to an application example.

Idioma originalInglés
Título de la publicación alojadaInformation Processing and Management of Uncertainty in Knowledge-Based Systems - 21st International Conference, IPMU 2026, Proceedings
EditoresBarbara Vantaggi, Davide Petturiti, Giulianella Coletti, Thierry Denoeux, Anne Laurent, Enrique Miranda, Jesús Medina, Bernadette Bouchon-Meunier, Ronald R. Yager
EditorialSpringer Nature
Páginas135-143
Número de páginas9
ISBN (versión impresa)9783032289995
DOI
EstadoPublicada - 2026
Evento21st International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2026 - Rome, Italia
Duración: 15 jun 202619 jun 2026

Serie de la publicación

NombreCommunications in Computer and Information Science
Volumen3021 CCIS
ISSN (versión impresa)1865-0929
ISSN (versión digital)1865-0937

Conferencia

Conferencia21st International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2026
País/TerritorioItalia
CiudadRome
Período15/06/2619/06/26

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