Robust design of a multi-objective closed-loop supply chain by integrating on-time delivery, cost, and environmental aspects, case study of a Tire Factory

Rising population and vehicle use resulted in an exponential growth of used tires generation which could cause significant disposal and environmental challenges. Thus, implementation of appropriate recycling or disposal practices has emerged as the critical challenge for the industries aiming to improve their environmental sustainability while satisfy the customers' needs and maintain the economic benefits. In this study, a multi-level closed-loop supply chain network is developed under deterministic and uncertain conditions to maximize the time delivery, and minimize total costs, and environmental impacts under the uncertainty of some parameters. A three-objective mixed integer linear programming model is proposed. The delivery time of purchased materials from suppliers to the manufacturing plants is maximized using the first objective function. The network overall profitability is maximized using the second objective function, and the negative environmental impacts are minimized using the third objective function. Furthermore, to overcome the innate uncertainty of the models' parameters, the Soyster and Mulvey approaches are applied. The developed model is implemented in a case study of a Tire Company. The results revealed the efficiency of on-time delivery considerations on the selection of internal and external suppliers. Applying the VIKOR method demonstrated the better performance of Soyster method compare to the Mulvey method. The results highlighted the performance of the proposed model in which the decision makers were enabled to decide among different types of suppliers (internal and external) based on the time delivery, total cost, and environmental impact. (C) 2020 Elsevier Ltd. All rights reserved.