Title:  Nonlinear Data Envelopment Analysis: An Algorithm and Application

Data Envelopment Analysis (DEA) has been proposed as an efficient method for aggregating metrics in the presence of multiple decision makers or entities. The literature so far has focused mainly on linear DEA models which have their limitations when it comes to studying complex systems. In this talk I will review DEA basic models and propose a new indefinite fractional bilinear DEA model and a branch-reduce-bound algorithm to solve it. We apply this new model to measuring sustainability in supply chain networks as well as preliminary results on measuring sustainability performance of power plants in the US.