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Rank Aggregation: Models and Algorithms

In: The Palgrave Handbook of Operations Research

Author

Listed:
  • Javier Alcaraz

    (Miguel Hernández University of Elche)

  • Mercedes Landete

    (Miguel Hernández University of Elche)

  • Juan F. Monge

    (Miguel Hernández University of Elche)

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 metaheuristicMetaheuristics 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.

Suggested Citation

  • Javier Alcaraz & Mercedes Landete & Juan F. Monge, 2022. "Rank Aggregation: Models and Algorithms," Springer Books, in: Saïd Salhi & John Boylan (ed.), The Palgrave Handbook of Operations Research, chapter 0, pages 153-178, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-96935-6_5
    DOI: 10.1007/978-3-030-96935-6_5
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    Cited by:

    1. Labbé, Martine & Landete, Mercedes & Monge, Juan F., 2023. "Bilevel integer linear models for ranking items and sets," Operations Research Perspectives, Elsevier, vol. 10(C).

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