for efficiency evaluation of some of the decision making units that have uncertain information, rough data envelopment analysis technique is used, which is derived from rough set theorem and data envelopment analysis (dea). in some situations rough data alter nonradially. to this end, this paper proposes additive rough–dea model and illustrates the proposed model by a numerical example.

The paper is devoted to the problem of generating artificial datasets for data envelopment analysis (DEA), which can be used testing DEA models and methods. In particular, papers that applied big often synthetic generation obtain large-scale because real large size, available in public domain, are extremely rare. This proposes algorithm takes as input some dataset complements it by efficient in...

The inverse Data Envelopment Analysis (InvDEA) is an exciting and significant topic in the DEA area. Also, uncertain data various real-life applications can degrade efficiency results. current work addresses InvDEA presence of stochastic data. Under maintaining score, inputs/outputs-estimation problem investigated when some or all its outputs/inputs increase. A novel optimality concept for mult...

Data Envelopment Analysis (DEA) provides means for piecewise linear approximation of production functions. To improve the fit to the data we propose to improve the flexibility of the frontier by extending DEA towards a more general piecewise quadratic approximation, called Quadratic Data Envelopment Analysis (QDEA). In contrast to the linear approximation, the quadratic approximation allows for...