Hybrid cluster and data envelopment analysis with interval data

Document Type: Article


1 Department of Industrial Engineering, Science and Research branch, Islamic Azad University, Tehran, Iran

2 Department of Mathematics, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran

3 3Department of Management, Shahid Beheshti University, Tehran, Iran

4 Department of Mathematics, Science and Research branch, Islamic Azad University, Tehran, Iran


Data envelope analysis (DEA) is an approach to estimate the relative efficiency of decision making units (DMUs). Several studies were conducted in order to prioritize efficient units and some useful models such as cross-efficiency matrix (CEM) were presented.  Besides, a number of DEA models with interval data have been developed and ranking DMUs with such data was solved. However, presenting an obtained crisp data derived interval data is a critical problem, so that many researches were implemented so as to compute weights and averaging the interval data. In this paper we propose the new algorithm to find more suitable weight applying a data mining approach of DMU’s data. For this purpose, we employed clustering and pair-wise comparison matrix on given relative efficiency from CEM. Results indicate there is meaningful different between efficiency of DMUs with lower bound and that of DMUs with upper bound.


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