there are several methods to ranking dmus in data envelopment analysis (dea) and candidates in voting system. this paper proposes a new two phases method based on dea’s concepts. the first phase presents an aspiration rank for each candidate and second phase propose final ranking.

We introduce a gradient descent algorithm for bipartite ranking with general convex losses. The implementation of this algorithm is simple, and its generalization performance is investigated. Explicit learning rates are presented in terms of the suitable choices of the regularization parameter and the step size. The result fills the theoretical gap in learning rates for ranking problem with gen...

Regularization schemes are frequently used for performing ranking tasks. This topic has been intensively studied in recent years. However, to be effective a regularization scheme should be equipped with a suitable strategy for choosing a regularization parameter. In the present study we discuss an approach, which is based on the idea of a linear combination of regularized rankers corresponding ...

introduction drastic model is an index and overlapping model that has been designed for producing vulnerability scores for different points by combining several thematic layers. overlapping distinguished methods are themost applicable methods for evaluatingvulnerability of aquifers because they are cheap, they can directly reach a defined goal, the used data in the methods are accessible or can...

This paper applies a new multi attribute decision-making (MADM) model to help companies for enterprise resource planning (ERP) selection problem based on Balanced Score Card method. This paper uses three-parameter interval grey numbers which is derived from Grey theory (was proposed by J. Deng). This numbers is used instead of linguistic variables. Beside, a new weighting method that outcomes f...

This paper applies a new multi attribute decision-making (MADM) model to help companies for enterprise resource planning (ERP) selection problem based on Balanced Score Card method. This paper uses three-parameter interval grey numbers which is derived from Grey theory (was proposed by J. Deng). This numbers is used instead of linguistic variables. Beside, a new weighting method that outcomes f...

We review techniques for optimizing stochastic discrete-event systems via simulation. We discuss both the discrete parameter case and the continuous parameter case, but concentrate on the latter which has dominated most of the recent research in the area. For the discrete parameter case, we focus on the techniques for optimization from a finite set: multiple-comparison procedures and ranking-an...

One main focus of learning theory is to find optimal rates of convergence. In classification, it is possible to obtain optimal fast rates (faster than n−1/2) in a minimax sense. Moreover, using an aggregation procedure, the algorithms are adaptive to the parameters of the class of distributions. Here, we investigate this issue in the bipartite ranking framework. We design a ranking rule by aggr...