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A novel inverse DEA-R model as for decision maker's preferences

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  • Javad Gerami
  • Mohammad Reza Mozaffari
  • Peter Wanke
  • Yong Tan

Abstract

In this paper, we present an innovative inverse data envelopment analysis (DEA) approach that incorporates ratio data. The proposed model simultaneously estimates the levels of inputs and outputs of decision-making units (DMUs) based on predetermined efficiency. Additionally, the model allows for assessing the levels of inputs and outputs according to the preferences of the decision maker (DM). The proposed model is nonlinear initially, but we transform it into a linear programming model. We demonstrate that the proposed model is always feasible. For the inverse DEA ratio-based (DEA-R) process, we adopt a two-step approach. Depending on the DM's preferences, we can employ different models in the inverse DEA-R process when dealing with ratio data. To illustrate the effectiveness of our approach, we present two numerical examples in the paper.

Suggested Citation

  • Javad Gerami & Mohammad Reza Mozaffari & Peter Wanke & Yong Tan, 2025. "A novel inverse DEA-R model as for decision maker's preferences," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 54(1), pages 89-134.
    • Handle: RePEc:ids:ijores:v:54:y:2025:i:1:p:89-134
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