A clustering approach for pairwise comparison matrices
  • Metaadatok
Tartalom: https://unipub.lib.uni-corvinus.hu/11152/
Archívum: Corvinus Kutatások
Gyűjtemény: Status = Published
Subject = Decision making
Type = Article
Cím:
A clustering approach for pairwise comparison matrices
Létrehozó:
Ágoston, Kolos Csaba
Bozóki, Sándor
Csató, László
Kiadó:
Taylor and Francis
Dátum:
2025
Téma:
Decision making
Tartalmi leírás:
We consider clustering in group decision making where the opinions are given by pairwise comparison matrices. In particular, the k-medoids model is suggested to classify the matrices since it has a linear programming problem formulation that may contain any condition on the properties of the cluster centres. Its objective function depends on the measure of dissimilarity between the matrices but not on the weights derived from them. Our methodology provides a convenient tool for decision support, for instance, it can be used to quantify the reliability of the aggregation. The proposed theoretical framework is applied to a large-scale experimental dataset, on which it is able to automatically detect some mistakes made by the decision-makers, as well as to identify a common source of inconsistency.
Nyelv:
angol
angol
Típus:
Article
PeerReviewed
Formátum:
application/pdf
Azonosító:
Ágoston, Kolos Csaba, Bozóki, Sándor ORCID: https://orcid.org/0000-0003-4170-4613 <https://orcid.org/0000-0003-4170-4613> and Csató, László ORCID: https://orcid.org/0000-0001-8705-5036 <https://orcid.org/0000-0001-8705-5036> (2025) A clustering approach for pairwise comparison matrices. Journal of the Operational Research Society, 76 (5). pp. 971-983. DOI 10.1080/01605682.2024.2406231 <https://doi.org/10.1080/01605682.2024.2406231>
Kapcsolat:
10.1080/01605682.2024.2406231