Abstract

Today, growth in the population and the use of vehicles have led to a growth in the production of waste tires and subsequently the creation of environmental concerns. Thus, choosing common strategies (such as retreading, recycling, burning, and disposal) to deal with these wastes and improve environmental conditions has become one of the most significant concerns of today's industries. In this study, a mixed-integer linear programming model has been used to develop a stochastic closed-loop supply chain network design (SCND). The proposed formulation has two objectives: (i) minimizing Eco-indicator 99 and (ii) maximizing profit in a multi-product, multi-echelon, and multi-period problem for tires. It is implemented in a practical case study in tire production industry. Also, uncertain parameters such as the return rate of products, demand, and the percentage of tire material provided by external suppliers are considered as possible scenarios. The improved version of the augmented ɛ-constraint, named AUGMECON2, is applied to solve the proposed problem. Finally, comprehensive sensitivity analysis is carried out to measure the efficiency. Obtained results represent that concerning global factors, an optimal closed-loop SCND can be very different and the problem is sensitive to the customs duty rate and exchange rate parameters. Besides, without considering the limitations of supplying raw materials by external suppliers, profits can increase by about 12%.

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