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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/19809

Title: Aggregation of Partial Rankings - An Approach Based on the Kemeny Ranking Problem
Authors: Napoles Ruiz, Gonzalo
Dikopoulou, Zoumpolia
Papageorgiou, Elpiniki
Bello, Rafael
Vanhoof, Koen
Issue Date: 2015
Publisher: Springer Verlag Berlin
Citation: Rojas, Ignacio; Joya, Gonzalo.; Catala, Andreu (Ed.). Advances in Computational Intelligence, p. 343-355
Series/Report: Lecture Notes in Computer Science
Series/Report no.: 9095
Abstract: Aggregating the preference of multiple experts is a very old problem which remains without an absolute solution. This assertion is supported by the Arrow's theorem: there is no aggregation method that simultaneously satisfies three fairness criteria (non-dictatorship, independence of irrelevant alternatives and Pareto efficiency). However, it is possible to find a solution having minimal distance to the consensus, although it involves a NP-hard problem even for only a few experts. This paper presents a model based on Ant Colony Optimization for facing this problem when input data are incomplete. It means that our model should build a complete ordering from partial rankings. Besides, we introduce a measure to determine the distance between items. It provides a more complete picture of the aggregated solution. In order to illustrate our contributions we use a real problem concerning Employer Branding issues in Belgium.
Notes: [Napoles, Gonzalo; Bello, Rafael] Univ Cent Marta Abreu Las Villas, Santa Clara, Cuba. [Napoles, Gonzalo; Dikopoulou, Zoumpoulia; Vanhoof, Koen] Hasselt Univ, Diepenbeek, Belgium. [Papageorgiou, Elpiniki] Technol Educ Inst Cent Greece, Lamia, Greece.
URI: http://hdl.handle.net/1942/19809
DOI: 10.1007/978-3-319-19222-2_29
ISI #: 000363699900029
ISBN: 9783319192215
ISSN: 0302-9743
Category: C1
Type: Proceedings Paper
Validation: ecoom, 2016
Appears in Collections: Research publications

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