Designing a multi-echelon closed-loop supply chain with disruption in the distribution centers under uncertainty

According to the need for further cost reduction and improving the process of the organization in the direction of customer demand, the concept of the supply chain has become increasingly significant and the organizations seek to expand this concept within their organizational framework. In this regard, efficient planning of distribution of products in the supply chain by considering disruption has received more attention recently. In this study a multi-objective mixed-integer linear programming model is developed for a green multi-echelon closed-loop supply chain network design under uncertainty. Moreover, a partial disruption is considered for distribution centers where has not been studied enough in previous works. The fuzzy credibility constraint approach is applied to cover uncertainty. In the following, the -constraint method is presented to solve and validate the model in small-sized instances. Moreover, a Non-dominated Sorting Genetic Algorithm is developed for solving the large-sized problems. Results show that uncertainty has a crucial impact on objective functions where the increase of objective functions by increasing the level of uncertainty, which was observed in all categories. Furthermore, the proposed NSGA-II is the best tool to deal with large-size problems where the EC method lacks the necessary efficiency.