 Ensemble ranking: Aggregation of rankings produced by different multi-criteria decision-making methodsMajid Mohammadi and Jafar Rezaei Omega, 2020, vol. 96, issue C Abstract: One of the essential problems in multi-criteria decision-making (MCDM) is ranking a set of alternatives based on a set of criteria. In this regard, there exist several MCDM methods which rank the alternatives in different ways. As such, it would be worthwhile to try and arrive at a consensus on this important subject. In this paper, a new approach is proposed based on the half-quadratic (HQ) theory. The proposed approach determines an optimal weight for each of the MCDM ranking methods, which are used to compute the aggregated final ranking. The weight of each ranking method is obtained via a minimizer function that is inspired by the HQ theory, which automatically fulfills the basic constraints of weights in MCDM. The proposed framework also provides a consensus index and a trust level for the aggregated ranking. To illustrate the proposed approach, the evaluation and comparison of ontology alignment systems are modeled as an MCDM problem and the proposed framework is applied to the ontology alignment evaluation initiative (OAEI) 2018, for which the ranking of participating systems is of the utmost importance. Keywords: MCDM; Half-quadratic; Ensemble ranking; Ontology alignment (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jomega:v:96:y:2020:i:c:s0305048319308448 Ordering information: This journal article can be ordered from DOI: 10.1016/j.omega.2020.102254 Access Statistics for this article Omega is currently edited by B. Lev More articles in Omega from Elsevier |
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