A Collaborative Stochastic Closed-loop Supply Chain Network Design for Tire Industry

Recent papers in the concept of Supply Chain Network Design (SCND) have seen a rapid development in applying the stochastic models to get closer to real-world applications. Regaring the special characteristics of each product, the stracture of SCND varies. In tire industry, the recycling and remanufacturing of scraped tires lead to design a closed-loop supply chain. This paper proposes a two-stage stochastic model for a closed-loop SCND in the application of tire industry. The first stage of model optimizes the expected total cost. Then, financial risk has been considered as the second stage of model to control the uncertainty variables leading to a robust solution. To solve the developed problem, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) have been used. To enhace the efficiency of metaheuristic algorithms, Response Surface Method (RSM) has been applied. Finally, the proposed model is evaluated by different test problem with different complexity and a set of metrics in terms of Pareto optimal solutions.