Optimal Planning of a Closed-loop Supply Chain with Recovery Options and Carbon Emission Considerations

Abstract

Climate change, increased carbon regulations, and globalized supply chains are driving industry practitioners and decision makers to implement various carbon policies to reduce carbon emissions. One of the effective approaches to mitigate carbon emissions is the implementation of closed-loop supply chain (CLSC). This paper proposes a deterministic mixed integer linear programming (MILP) model for a multi-period and multi-product closed loop supply chain network with multiple recovery, quality returns and carbon emission considerations. Transportation mode selection decision for logistic activities is also incorporated in the model. Results show that the model captures trade-offs between the total cost and carbon emission. Further, results suggest that carbon price directly effects on the total cost. Conversely, in carbon trading policy, due to having carbon buying and selling flexibility, both total cost and carbon emission are significantly reduced. Sensitivity analysis shows that the operational costs of various recovery activities impact on the total cost. This study provide evidence that besides achieving optimal closed-loop supply chain network design (CLSCND) and planning, it also reduces carbon emissions significantly without increasing the total cost.