A fuzzy data envelopment analysis method for performance evaluation of renewable feedstock suppliers

Abstract

The growing energy consumption in the world caused the human’s tendency is faster to find new ways of energy production. One of the most important new energy sources is production of biodiesel from Microalgae. Microalgae is regarded as a renewable feedstock for biodiesel production and has drawn the attention to a wide range of researches in recent years due to containing high content of non-edible oil for biodiesel production. In this study, we investigate growth indicators of algae cultivation for assessing the efficiency of the candidate locations for algae cultivation under uncertainty. We extend a new fuzzy data envelopment analysis (FDEA) model for finding the optimum candidate among the available alternatives. The proposed model is, in fact, a non-radial and non-oriented model which evaluates each candidate under uncertainty. We also formulate an equivalent crisp linear programming problem with the aim of solving the suggested FDEA model under various levels of uncertainty. We provide a real case study in Iran to validate the proposed approach.