Multiple objective programming model to solve voting system by data envelopment analysis with common set of weights

Multiple objective programming model to solve voting system by data envelopment analysis with common set of weights

Ranking a system of voting is an important topic in DEA. Many firms apply voting systems to rank candidates. Generally, these kinds of methods rank candidates by their associated weights. In this paper, to increase discrimination power among candidates, a novel model for obtaining a suitable value of discriminating factor is proposed. Then, using the optimal value of the discriminating factor, a new model for calculating preference scores of candidates is presented. This model evaluates candidates based on different set of weights. To evaluate candidates based on common set of weights (CSW), using concept of ideal point, two new multiple objective programming models are proposed.

Ranking a system of voting is an important topic in DEA. Many firms apply voting systems to rank candidates. Generally, these kinds of methods rank candidates by their associated weights. In this paper, to increase discrimination power among candidates, a novel model for obtaining a suitable value of discriminating factor is proposed. Then, using the optimal value of the discriminating factor, a new model for calculating preference scores of candidates is presented. This model evaluates candidates based on different set of weights. To evaluate candidates based on common set of weights (CSW), using concept of ideal point, two new multiple objective programming models are proposed.