the ways of placing decision making units (dmus) in certain clusters are found as a subject in statistics, these ways usually are heuristic. the proposed clustering approach in this article considers preferences of dmus. this study applies data envelopment analysis (dea) dmus are clustered by solving multi-objective linear problem (molp) and by considering preferences of each dmu at production ...

The Malmquist index (MI) has demonstrated its usefulness in comparing the performances of Decision Making Units (DMUs) performances. global MI (GMI) been suggested as a means to overcome three drawbacks MI: non-circularity, disparate measurements, and infeasibility. Recently, it appeared that can also be used compare groups DMUs. While this new function increased usefulness, presents same MI. I...

As a useful management and decision tool, data envelopment analysis (DEA) has become a pop area of research. One of the topics of interests in DEA is sensitivity and stability analysis of decision making units (DMUs). Due to the uncertainty of the data in real life, this paper will give some DEA models in fuzzy environment. It is followed by a series analysis of sensitivity and stability for al...

In this study, both optimistic and pessimistic approaches of data envelopment analysis are applied to propose an equitable ranking method in fuzzy environments. To this end, we suppose that the sum of efficiency scores of all decision making units (DMUs) equals to unity. Using the worst-best and best-worst approaches, the minimum and maximum possible efficiency scores of each DMU are estimated ...

Data envelopment analysis (DEA) is known as a useful tool that produces many efficient decision-making units (DMUs). Traditional DEA provides relative efficient scores and reference sets, but does not influence and rank the efficient DMUs. This paper suggests a method that pro‐ vides influence and ranking information by using Pag‐ eRank as a centrality of Social Network analysis (SNA) based on ...

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 the...

in this paper, by introducing two virtual decision-making units (dmus) called ideal dmu (idmu) and anti-ideal dmu (admu) with fuzzy inputs-outputs, the efficiency evaluation of dmus are done by fuzzy data envelopment analysis (fdea). therefore, we evaluate dmus from the perspective of the best and worst possible relative efficiency. for each dmu two efficiencies are calculated while inputs and ...

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...