A Stochastic Multi-Objective Model for a Sustainable Closed-Loop Supply Chain Network Design in the Automotive Industry

This paper aims to develop a sustainable closed-loop supply chain network model with a modular single product which is specifically designed for the automotive industry. Drawing upon sustainability criteria, three objective functions are formulated for the closed-loop network design problem including maximizing total profit across the network, minimizing the effects of environmental pollutants and maximizing employments created by the establishment of the required facilities and also maximizing the weighted sum of the minimum distance of facilities from the residential areas. In order to validate the research, a case study of the Iran's automotive industry is also conducted. In addition, a scenario-based approach which applies the stochastic programming is used to cope with the uncertainty in both the demand and the amount of returned unusable vehicles. The results show that the stochastic programming approach is successful in mitigating the effects of uncertainties. Moreover, augmented epsilon-constraint methods are applied to deal with the proposed model. The preferred Pareto optimal solution achieves a 55.1% decrease in the environmental objective value, with only 0.2% increase in the economic objective value relative to the corresponding optimal value.

Automated summary

This study aims to develop a sustainable closed-loop supply chain network model for the automotive industry and formulates three objective functions based on sustainability criteria. A case study of Iran's automotive industry is used for validation, and a scenario-based approach using stochastic programming is applied to handle uncertainties. The results show that the stochastic programming approach is successful in mitigating the effects of uncertainties and the preferred Pareto optimal solution achieves a significant decrease in environmental impact with minimal increase in economic value.