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

Mathematical and Computational Applications

Jahanshahloo, Gholamreza¹ 

关键词: Data envelopment analysis (DEA);    Ranked voting data;    Ranking of c;    idates;    Common weight;   

DOI  :  10.3390/mca17010001

学科分类：计算数学

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY