A coevolutionary algorithm for exploiting a large fuzzy outranking relation

Jesús Jaime Solano Noriega, Juan Carlos Leyva López, Carlos Andrés Oñate Ochoa and José Rui Figueira

European Journal of Operational Research, 2025, vol. 323, issue 2, 540-552

Abstract: The outranking approach in Multiple Criteria Decision Analysis (MCDA) uses ranking procedures to exploit a fuzzy outranking relation, which captures the decision maker's notion of a ranking. However, as decision problems become more complex and computer performance improves, new ranking procedures are needed to rank complex data sets that decision-makers may not interpret. This paper discusses recent efforts and potential directions for developing ranking procedures that use multiobjective evolutionary algorithms (MOEAs) to exploit a fuzzy outranking relation. After that, based on the cooperative coevolutionary algorithms (CCEA) approach, we suggest some fundamental modifications to extend the RP2-NSGA-II+H algorithm that improve the scalability of this MOEA to exploit large-sized fuzzy outranking relations. Empirical results indicate that adjustments improve the RP2-NSGA-II+H algorithm for the addressed problem. The proposed ranking procedure outperforms RP2-NSGA-II+H in terms of ranking error rates based on the experiments conducted. Our experimental results also demonstrate that the proposed approach can be scaled for instances of the ranking problem of up to one thousand alternatives.

Keywords: Multiple criteria decision analysis; Fuzzy outranking relations; Multiobjective evolutionary algorithms; Cooperative coevolutionary algorithms; Ranking procedures (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221724009536
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:323:y:2025:i:2:p:540-552

DOI: 10.1016/j.ejor.2024.12.012

Access Statistics for this article

European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().