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Rank Aggregation: Models and Algorithms

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The Palgrave Handbook of Operations Research

Abstract

In today’s society, in which a large amount of information of all kinds is collected daily, the aggregation of rankings is becoming a necessary task to provide us with significant knowledge for decision-making. Rank aggregation consists, in general terms, of developing a ranking of a set of elements, based on multiple ranked lists, so that the final ranking is able to combine the information contained in the available rankings. From a mathematical point of view, ranking aggregation problems are combinatorial optimization problems and different types of techniques have been proposed to solve them: exact, heuristic and also metaheuristic approaches. In this chapter, we review some of the most well-known ranking aggregation problems that can be grouped into two broad categories: rankings of elements and rankings of sets. Each of the problems is formally described and then some of the techniques proposed for their resolution are discussed. Illustrative examples are presented throughout the chapter to facilitate understanding of the different problems.

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Acknowledgements

The authors thank the grant PID2019-105952GB-I00 funded by Ministerio de Ciencia e Innovación/Agencia Estatal de Investigación /10.13039/501100011033. This work was partially also supported by the Generalitat Valenciana under grant PROMETEO/2021/063.

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Authors and Affiliations

  1. Center of Operations Research, Miguel Hernández University of Elche, Elche (Alicante), Spain

    Javier Alcaraz, Mercedes Landete & Juan F. Monge

Authors
  1. Javier Alcaraz
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  2. Mercedes Landete
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  3. Juan F. Monge
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Corresponding author

Correspondence to Mercedes Landete .

Editor information

Editors and Affiliations

  1. Kent Business School, University of Kent, Canterbury, UK

    Saïd Salhi

  2. Lancaster University, Lancaster, UK

    John Boylan

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Alcaraz, J., Landete, M., Monge, J.F. (2022). Rank Aggregation: Models and Algorithms. In: Salhi, S., Boylan, J. (eds) The Palgrave Handbook of Operations Research . Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-96935-6_5

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