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Use este identificador para citar ou linkar para este item: https://repositorio.ufpe.br/handle/123456789/38287

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Título: Random-subset voting
Autor(es): AMORIM, Guilherme Barros Corrêa de
Palavras-chave: Engenharia de Produção; Métodos de votação; Votação probabilística; Racionalidade limitada; Teoria da decisão
Data do documento: 5-Mai-2020
Editor: Universidade Federal de Pernambuco
Citação: AMORIM, Guilherme Barros Correa de. Random-subset voting. 2020. Tese (Doutorado em Engenharia de Produção) - Universidade Federal de Pernambuco, Recife, 2020.
Abstract: Most of the voting procedures in the literature assume that voters have preferences that are complete, transitive and subject to the independence of irrelevant alternatives property. A basic premise concerning the rationality of the individuals is that any voter is able to evaluate any pair of alternatives in a set and select his/her preferred one, or indicate indifference between them. Nevertheless, some researchers have highlighted that voters, as humans, have limited capacity to deal with and consequently compare big sets of alternatives. In this study, we propose the Random-Subset Voting (RSV), a voting procedure that allows the voters to evaluate less alternatives. Instead of analyzing the entire choice set, each voter evaluates a random subset of a pre-determined size. The proposed model was tested under Borda with three different approaches: mathematical modelling, Monte Carlo simulations and experiments. It was also tested under plurality, approval and Condorcet with Monte Carlo simulations. The results for all methods suggest that, for big and homogeneous populations, the proposed model leads to equivalent results to those found in the traditional methods, having the advantage of allowing the voters to make decisions by analyzing less options. We advocate that RSV can be a tool to be implemented in our societies and in our organizations, having important social and economic implications.
URI: https://repositorio.ufpe.br/handle/123456789/38287
Aparece nas coleções:Teses de Doutorado - Engenharia de Produção

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