Uniquely classifying flexible measures by a CWS model
Subject Areas : Statistics
m.
korzedin
1
(Department of power engineering, Brandenburg Technical University, Germany)
m.
mirbolouki
2
(Departments of Applied Mathematics, Islamic Azad University, Imam Khomeini's Branch, Tehran, Iran)
Keywords: تحلیل پوششی دادهها, ورودی و خروجی, عوامل انعطافپذیر, مدل وزن مشترک,
Abstract :
Data Envelopment Analysis (DEA) deals with evaluating a set of decision-making units (DMUs) based on nonparametric mathematical approaches. In classical DEA models, the given set of factors of DMUs is divided into two categories, inputs and outputs, while in some practical problems there are some measures whose membership to these categories is unclear. It means these factors treat different input or output roll for various DMUs. This kind of factors is known as a flexible measure. The proposed models for this purpose are DMU-oriented in which each DMU evaluate its efficiency and classify flexible measures for all other DMUs regards to its benefit. This classification may not be optimal for every DMUs. In this paper, we present a model based on a common set of weights (CSW). The advantage of the proposed model is to classify flexible measures uniquely for all DMUs. At the end of paper, the proposed model is applied in an example of wind power farms.
