Designing a closed-loop supply chain for reusable packaging materials: A risk-averse two-stage stochastic programming model using CVaR

Abstract

Reusable packaging material (RPM) provide a circular and sustainable way of transporting parts/products safely along the various stages of supply chain. In the present work, we study a multi-echelon closed-loop supply chain network design problem for wooden RPMs. Initially, a mixed-integer programming model under deterministic setting is proposed to determine the optimal configuration of the manufacturing facilities and distribution centers of RPMs. Further, a risk-averse two-stage stochastic programming model is developed to incorporate the uncertainties associated with the demand, initial inventory and level of reusability of the RPMs. The developed model utilizes conditional-value-at-risk (CVaR) as risk measure since it provides more robust solutions compared to a risk-neutral approach in presence of uncertainty. The applicability of the model is explained using a real-life example of the prevalent supply chain of wooden pallets in several automobile manufacturers and their suppliers in India. The results suggest trade-off among various cost components such as fixed cost of opening facilities and capacity installation, manufacturing, acquisition, refurbishing, and environmental cost. Several managerial insights are drawn by carrying out sensitivity analysis of deterministic model and running the stochastic model with different values of CVaR parameters. Finally, we present numerical results to discuss how incorporating a risk measure affects the computational performance and solution of the CVaR model.