Data envelopment analysis approach for discriminating efficient candidates in voting systems by considering the priority of voters

Abstract

There are different ways to allow the voters to express their preferences on a set of candidates. In the traditional voting systems, it is assumed that the votes of all voters have the same importance and there is no preference between them. In this paper, a new approach is proposed to express the preference of voters on a set of candidates. In the proposed approach voters are classified into several categories with different importance levels in which the vote of a higher category may have a greater importance than that of the lower category. Then two models are introduced to measure the best preference scores of the target candidate from the virtual best candidate and the virtual worst candidate point of view. After that, two obtained preference scores are aggregated together in order to obtain an overall ranking. Finally, two numerical examples are provided for illustration the applications of the proposed approach.