Optimal PET Recycling Management; Applying the Conditional Value-at-Risk (CVaR) Approach under Uncertainty for a Real Case

In the pursuit of sustainable development goals, recycling has attracted a high level of attention around the world due to its economic and environmental benefits; however, applying the Conditional Value-at-Risk (CVaR) as an effective risk management approach for optimal Design of reverse supply chain (RSC) has been addressed by a few studies. This study mainly aims to achieve an optimal design for the RSC of recycling of polyethylene terephthalate (PET) bottles due to uncertainties in the market price of recycling materials, logistics costs, and the supply of raw materials. Considering the stochastic nature of the waste RSC parameters, two-stage stochastic programming models are developed in which the CVaR(Shortage) is utilized as a risk criterion to control shortages in demand centers. Moreover, the expected value of profit (E(Profit)) and the CVaR(Profit) are considered as two different objective functions. To evaluate efficiency and applicability, our selected models are implemented with the real data of Tehran’s Municipal Waste data. Comparing the empirical results indicate that using the CVaR(shortage) is an appropriate and reasonable approach to tackle the risk of a shortage in demand centers, and can be used to design the supply chain of other case studies. Also, the CVaR(Profit)) is more conservative in the face of the risk of shortage due to the risk-taking feature embedded in the objective function, which can be adjusted in accordance with the decision maker’s preference. The results additionally indicate that transportation cost plays an essential role in the cost structure of PET recycling stages.