A procedure for ranking efficient units in data envelopment analysis
Management Science
A Complete Efficiency Ranking of Decision Making Units in Data Envelopment Analysis
Computational Optimization and Applications
Data Envelopment Analysis: Theory, Methodology, and Application
Data Envelopment Analysis: Theory, Methodology, and Application
Idea and Ar-Idea: Models for Dealing with Imprecise Data in Dea
Management Science
Ranking of units on the DEA frontier with common weights
Computers and Operations Research
Journal of Computational and Applied Mathematics
Ranking of units by positive ideal DMU with common weights
Expert Systems with Applications: An International Journal
Common weights for fully ranking decision making units by regression analysis
Expert Systems with Applications: An International Journal
A cross-dependence based ranking system for efficient and inefficient units in DEA
Expert Systems with Applications: An International Journal
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In the last decade, ranking units in data envelopment analysis (DEA) has become the interests of many DEA researchers and a variety of models were developed to rank units with multiple inputs and multiple outputs. These performance factors (inputs and outputs) are classified into two groups: desirable and undesirable. Obviously, undesirable factors in production process should be reduced to improve the performance. Also, some of these data may be known only in terms of ordinal relations. While the models developed in the past are interesting and meaningful, they didn't consider both undesirable and ordinal factors at the same time. In this research, we develop an evaluating model and a ranking model to overcome some deficiencies in the earlier models. This paper incorporates undesirable and ordinal data in DEA and discusses the efficiency evaluation and ranking of decision making units (DMUs) with undesirable and ordinal data. For this purpose, we transform the ordinal data into definite data, and then we consider each undesirable input and output as desirable output and input, respectively. Finally, an application that shows the capability of the proposed method is illustrated.