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An optimization-based approach to ranking aggregation with weak order outputs

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dc.contributor.authorAledo, Juan A.
dc.contributor.authorLandete, Mercedes
dc.contributor.authorDomínguez Sánchez, Concepción
dc.contributor.authorJaime Alcántara, Juan de Dios
dc.contributor.departmentEstadística e Investigación Operativa
dc.contributor.otherFacultades de la UMU::Facultad de Matemáticas
dc.date.accessioned2026-05-14T10:11:23Z
dc.date.available2026-05-14T10:11:23Z
dc.date.issued2026
dc.description.abstractRank aggregation problems combine individual orderings of a common set of items into a consensus ranking reflecting collective preferences. This paper introduces a general Integer Linear Programming (ILP) framework to model and solve aggregation problems whose solutions are weak orders (bucket orders). The framework provides a flexible and tractable architecture that incorporates structural and normative constraints required in practice. Within this setting, we develop several ILP formulations embedding additional structural requirements on the consensus bucket order, including a fixed number of buckets, predefined bucket sizes, top-$k$ constraints, and group-based fairness conditions. The formulations are modular and adaptable to different aggregation contexts. A particularly relevant case is the Optimal Bucket Order Problem (OBOP), for which we present the first exact mixed-integer linear programming formulation. We evaluate the models through computational experiments, comparing optimal solutions with the heuristics of Aledo et al.\ (2018) and assessing scalability on benchmark instances from the PrefLib library. Finally, we present a real-world case study on Spanish universities, where the proposed models aggregate competing rankings under structural and fairness constraints.
dc.formatapplication/pdf
dc.format.extent39
dc.identifier.urihttp://hdl.handle.net/10201/231981
dc.languageeng
dc.relationConcepción Domínguez and Mercedes Landete were supported by project PID2021-122344NB-I00, funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”. Concepción Domínguez was also supported by project PID2024-156594NB-C21, funded by MCIU/AEI/ 10.13039/501100011033 and by ERDF/EU, and by Generalitat Valenciana under project Emergent CIGE/2024/132. Juan de Dios Jaime-Alcántara and Mercedes Landete were also supported by grant CIPROM/2024/34, funded by the Conselleria de Educación, Cultura, Universidades y Empleo, Generalitat Valenciana. Juan A.\ Aledo was supported by SBPLY/21/180225/000062 (Junta de Comunidades de Castilla-La Mancha and ERDF A way of making Europe), PID2022-139293NB-C32 (MICIU/AEI/10.13039/501100011033 and ERDF, EU) and 2025-GRIN-38476 (Universidad de Castilla-La Mancha and ERDF A way of making Europe).
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectRanking Aggregation
dc.subjectOptimal Bucket Order Problem
dc.subjectFairness
dc.subjectInteger Programming
dc.subject.odsObjetivo 16: Paz y justicia
dc.titleAn optimization-based approach to ranking aggregation with weak order outputs
dc.typeinfo:eu-repo/semantics/preprint
dc.type.versioninfo:eu-repo/semantics/submittedVersion
dspace.entity.typePublicationes
relation.isAuthorOfPublication7def9d87-68e7-45d4-bf1f-bb994bd2608e
relation.isAuthorOfPublication979401f5-8cd0-404c-9735-0e4e67bef6d0
relation.isAuthorOfPublication.latestForDiscovery7def9d87-68e7-45d4-bf1f-bb994bd2608e
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