Novel criterion models in the inverse DEA problem
by Mojtaba Ghiyasi
International Journal of Operational Research (IJOR), Vol. 35, No. 1, 2019

Abstract: This article deals with 'inverse' data envelopment analysis (DEA) problem which is a mathematical programming-based technique. The process of checking perturbed DMUs is simplified by proposing a new criterion model. This yields to a reduction of computational complexity for the criterion model. In addition, more realistic criterion model is also proposed and the relationship between existing criterion model and proposed models are discussed. Moreover, it is shown that proposed models solve some problematic failures of the existing inverse DEA models in the literature. Two numerical examples are provided to illustrate the idea. The proposed model are illustrated by a real life data and a comparison between existing criterion model in the literature and proposed criterion models is also provided.

Online publication date: Thu, 09-May-2019

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