Manufacturers are devising new methods to make their production systems more efficient and effective. Designing an optimized supply chain can support the corresponding processes to integrate the resources. However, one of the most important obstacles is the resource limitation. Recycling the second-hand products is one of the approaches to cope with this issue. Reverse logistics is a system of collecting products from end-users to the manufacturing centers for obtaining values from collected materials. In this research, the collection and distribution process of engine oil, which is derived from one of the most valuable natural resources, is considered. A mixed-integer linear programming model for a closed-loop supply chain of used engine oil is proposed and a case study of an oil refinery company is proposed to explore the applicability of the model. Due to uncertainty in the amounts of collected oil in the engine oil reverse logistics, the robust optimization approach is chosen to deal with uncertainty. Two objective functions of maximizing profit and minimizing the risk of the collection are considered. To solve the bi-objective model, augmented epsilon-constraint approach is utilized. The results depict the merit of the current research. (C) 2017 Elsevier Ltd. All rights reserved.