Three new models for preference voting and aggregation

Y. M. Wang, K. S. Chin, J. B. Yang

    Research output: Contribution to journalArticlepeer-review


    Preference voting and aggregation require the determination of the weights associated with different ranking places. This paper proposes three new models to assess the weights. Two of them are linear programming (LP) models which determine a common set of weights for all the candidates considered and the other is a nonlinear programming (NLP) model that determines the most favourable weights for each candidate. The proposed models are examined with two numerical examples and it is shown that the proposed models cannot only choose a winner, but also give a full ranking of all the candidates. © 2007 Operational Research Society Ltd. All rights reserved.
    Original languageEnglish
    Pages (from-to)1389-1393
    Number of pages4
    JournalJournal of the Operational Research Society
    Issue number10
    Publication statusPublished - Oct 2007


    • Borda-Kendall method
    • Data envelopment analysis (DEA)
    • Preference aggregation
    • Preference voting


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