Using slacks-based model to solve inverse DEA with integer intervals for input estimation

Abstract This paper deals with an inverse data envelopment analysis (DEA) based on the non-radial slacks-based model in presence of uncertainty employing both integer and continuous interval data. To this matter, suitable technology formulation for DEA are proposed using arithmetic partial orders numbers. The is discussed from following question: if output $$DMU_o$$ D M U o increases $$Y_o$$ Y to $$\beta _o$$ β , such new DMU given by $$(\alpha _o^*,\beta )$$ ( α ∗ , ) belongs technology, its inefficiency score not less than t-percent, how much should inputs increase? A offered respond previous question, whose Pareto solutions characterized solution a related multiple-objective nonlinear programming (MONLP). Necessary sufficient conditions input estimation when increased. functional example presented illustrate methodology, variables.