Full Ranking of Decision Making Units by Relaying Hyperplane on the Set of Produce Possibility

The exit methods for producing common weight in DEA are complicated or they can’t produce full ranking for Decision Making Units (DMUs). Wang and et al introduced two methods based on regresion analysis for finding common weights. In these method they fined set of common weight so that the efficeincy which is computed by set of common weight for all units, are always smaller or and equal to obtained optimistic efficeincy from CCR model. In this methods we are trying to make the computed efficeincy by common weight closer to obtained optimistic efficeincy from CCR model, and or in other words the goal of obtaining unique hyperplane as all distance of DMUs from this hyperplane will be minimal. In this paper by using an example, we show that the obtained hyperplane from suggested methods of Wang is passing throug PPS. In other words, in introduced method of proposed hyperplane for ranking, isn’t relaying PPS, neccessarly. At the end, we introduce a new method for ranking the decision makind units that is a correspond hyperplane of relaying common weight set on PPS and finally we can use this techniqe for real data.

Keywords:

Data envelopment analysis , Ranking efficeincy , Optimistic efficeincy , Set of common weight