On Data Envelopment Analysis Framework for Optimizing Two-Stage Systems Under Neutrosophic Environment

Recently, DEA became one of the evaluation method and used widely by the researchers for the analysis. It’s used to evaluate units under evaluation that produce multiple outputs by consuming multiple inputs This paper presents a neutrosophic set-based, two-stage DEA framework to surmount the weak linkages within the traditional DEA model when uncertainties and imprecise values exist. Neutrosophic sets capture the uncertainty by considering membership degrees of truth, indeterminacy, and falsity. Overall, this framework decomposes overall system efficiency into stage efficiencies and provides deep insights into the system performance. We developed a two-stage DEA optimization model with neutrosophic variables and constraints. This framework can apply to any organization in order to support decision-makers to make rational decisions and allocate resources optimally, especially in the modern competitive business environment. A case study introduced to show how the model could handle neutrosophic uncertainty, and the mathematical formulation presents succinctly for practical implementation.