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Article

A Method for Discriminating Efficient Candidates with Ranked Voting Data by Common Weights

by
Gholamreza Jahanshahloo
,
Farhad Hosseinzadeh Lotfi
,
Masomeh Khanmohammadi
* and
Mansoureh Kazemimanesh
Department of Mathematics Science and Research Branch,Islamic Azad University,Tehran, Iran
*
Author to whom correspondence should be addressed.
Math. Comput. Appl. 2012, 17(1), 1-8; https://doi.org/10.3390/mca17010001
Published: 1 April 2012

Abstract

Ranked voting data arise when voters select and rank more than one candidate with an order of preference. Cook et al.[1] introduced data envelopment analysis (DEA) to analyze ranked voting data. Obata et al.[2] proposed a new method that did not use information obtained from inefficient candidates to discriminate efficient candidates. Liu et al.[3] ranked efficient DMUs on the DEA frontier with common weights. They proposed a methodology to determine one common set of weights for the performance indices of all DMUs. Then, these DMUs were ranked according to the efficiency score weighted by the common set of weights. In this paper, we use one common set of weights for ranked voting data.
Keywords: Data envelopment analysis (DEA); Ranked voting data; Ranking of candidates; Common weight Data envelopment analysis (DEA); Ranked voting data; Ranking of candidates; Common weight

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MDPI and ACS Style

Jahanshahloo, G.; Lotfi, F.H.; Khanmohammadi, M.; Kazemimanesh, M. A Method for Discriminating Efficient Candidates with Ranked Voting Data by Common Weights. Math. Comput. Appl. 2012, 17, 1-8. https://doi.org/10.3390/mca17010001

AMA Style

Jahanshahloo G, Lotfi FH, Khanmohammadi M, Kazemimanesh M. A Method for Discriminating Efficient Candidates with Ranked Voting Data by Common Weights. Mathematical and Computational Applications. 2012; 17(1):1-8. https://doi.org/10.3390/mca17010001

Chicago/Turabian Style

Jahanshahloo, Gholamreza, Farhad Hosseinzadeh Lotfi, Masomeh Khanmohammadi, and Mansoureh Kazemimanesh. 2012. "A Method for Discriminating Efficient Candidates with Ranked Voting Data by Common Weights" Mathematical and Computational Applications 17, no. 1: 1-8. https://doi.org/10.3390/mca17010001

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