A directional distance function approach for Ranking voting system

By using Data Envelopment Analysis (DEA) Cook and Kress have proposed a method for estimating preference scores without imposing any fixed weights from outset. The principal weaknesses of this procedure are how to choose the discrimination intensity functions and that several candidates are often efficient. In this paper we proposed a new method based on direction distance function (DDF) that can ranking efficient candidate. For avoided to choose the discrimination intensity functions in this method we consider d (.,ε)= 0

Keywords:

Data Envelopment Analysis , Voting System , Ranking direction distance function