A multi-objective, multi-echelon green supply chain network design problem with risk-averse retailers in an uncertain environment

This paper proposes a new multi-objective, multi-echelon supply chain network design problem. The proposed framework is green, in which it tackles the demand uncertainty of a product, environmental uncertainties, and the downstream risk attitude into the problem formulation. In this way, the demand uncertainty is taken into account through the Conditional Value at Risk (CVaR) method which, in turn, relies on the data driven approach. On the other hand, uncertainty set approach is employed to deal with the environmental uncertainties, i.e. CO2 emissions. Proposition of such a green supply chain network, based on the aforementioned uncertainties, makes the proposed model realistic, which is what completely missing in the literature. In order to proceed with this model, a robust counterpart of the developed uncertain problem should be formulated. The augmented epsilon-constraint method is used to transform the developed multi-objective mathematical programming problem into a single-objective one. This may give rise to the global optimal solution through the exact mathematical solution method. Simulation results demonstrate the efficiency of the proposed framework. (C) 2017 Sharif University of Technology. All rights reserved.