Introduction to the Theory and Application of Data Envelopment Analysis: A Foundation Text with Integrated Software
Data Envelopment Analysis: Theory, Methodology and Application
Data Envelopment Analysis: Theory, Methodology and Application
Data Envelopment Analysis: A Comprehensive Text with Models, Applications References, and DEA-Solver Software with Cdrom
A generalized DEA model for inputs/outputs estimation
Mathematical and Computer Modelling: An International Journal
Right and left returns to scales in data envelopment analysis: Determining type and measuring value
Computers and Industrial Engineering
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This paper studies the inverse Data Envelopment Analysis (inverse DEA) for the case of variable returns to scale (inverse BCC). The developed inverse BCC model can preserve relative efficiency values of all decision making units (DMUs) in a new production possibility set composing of all current DMUs and a perturbed DMU with new input and output values. We consider the inverse BCC model for a resource allocation problem, where increases of some outputs and decreases of the other outputs of the considered DMU can be taken into account simultaneously. The inverse BCC problem is in the form of a multi-objective nonlinear programming model (MONLP), which is not easy to solve. We propose a linear programming model, which gives a Pareto-efficient solution to the inverse BCC problem. However, there exists at least an optimal solution to the proposed model if and only if the new output vector is in the set of current production possibility set. The proposed approach is illustrated via a case study of a motorcycle-part company.