Proposing a multi-objective multi-echelon closed-loop supply chain model with the possibility of partial disruption in distribution centers and maximizing network reliability

Nowadays, given the competitive environment of business world, designing a supply chain (SC) that is compatible with the needs of the consumer market seems crucial. Due to its long-term impact on the company's performance, making decisions related to fulfilling the customer demand is an important issue in SC design and management. The present research tries to design a closed- loop supply chain network (SCN) with possible partial disruption in distribution centers during servicing. The objectives of this model are to minimize the total cost of SCN and maximize the system reliability, which is, in turn, dependent on the strategy chosen to cope with the partial disruption. Thus, in case of a partial disruption, some centers should be selected to compensate for disruption that, in addition to reducing costs, will be able to increase the system reliability. A weighted goal programming approach is used for solving the proposed multi- objective model, and a non-dominated sorting genetic meta-heuristic algorithm along with the exact method are developed in order to solve the problem. The results indicated that the proposed algorithm has appropriate performance in achieving near-exact solutions in large scales problems.