Recently two important methods [ \Area ranking of fuzzy numbers based on positive and negative ideal points", Computers and Mathematics with Applications, pp. 1769-1779 (2009)] have been proposed for ranking fuzzy numbers. But we have found that they both have a same basic disadvantage. In this paper, after a short review on diierent proposed fuzzy number ranking methods, we explain the drawbac...

this paper introduces a new method for incorporating the performance of alternatives into their ultimate ranking in a linear assignment method. this method is one of multi-criteria decision-making methods, in which the weight of criteria is incorporated in ranking the alternatives, and the distance between the performances of alternatives do not affect in ranking the alternatives. in order to m...

There exist many different ranking methods for ranking efficient Decision Making Units (DMUs) in Data Envelopment Analysis (DEA). However, since each of these methods considers a certain theory for ranking, they may give different ranks. In practice, choosing a ranking method, the results of which the Decision Maker (DM) would be able to trust is an important issue. In this paper, we consider s...

in many applications, ranking of decision making units (dmus) is a problematic technical task procedure to decision makers in data envelopment analysis (dea), especially when there are extremely efficient dmus. in such cases, many dea models may usually get the same efficiency score for different dmus. hence, there is a growing interest in ranking techniques yet. the purpose of this paper is ra...

Today, all countries publish many scientific studies in order to make progress a sense and plan for the future. Many criteria, such as impact factor, citation count, article score, have been developed measure, compare, rank quality of journals which these are published. These criteria used purposes academic promotion, hiring, publication support, project scholarships. It is extremely important ...

  In this paper, presenting two simple methods for ranking of efficient DMUs in DEA models that included to add one virtual DMU as ideal DMU and is using the additive model. Note that, we use an ideal point just for comparing efficient DMUs with. Although these methods are simple, they have ability for ranking all efficient DMUs, extreme points and the others, also they are capable of ranking t...

Probability of default estimation via machine learning on historical data is widely studied in credit risk modeling. In this work, we investigated the use for a finer-grained task, namely spot factoring. Here, goal to estimate likelihood that an invoice will be paid acceptable timeframe. case, more related overdueness invoice. Based observation, investigate three possible tasks estimating risk:...