Multi-facility-based improved closed-loop supply chain network for handling uncertain demands

Globalization has enlightened market with both opportunity and risk by bringing a more connected business environment, which ensures more customers and new markets. In contrast, it also brought a larger extent of competitors. The more collaborative environment can help companies to focus on their core competence to simultaneously reduce cost and participate more profitably in their trade. Uncertainty is a major outcome of the globalization process; firms are developing new methods and strategies to deal with risk and take control of uncertainty factors. This work introduces a novel approach that could help in collecting the end-of-life and end-of-use products from the end-users. These collected products enter the value chain and help in reducing the overall cost of the supply chain. A mixed-integer linear programming model has been formulated to assess the overall cost of the supply chain for the presented study. Due to the NP-hardness of the problem, few well-known metaheuristics and hybrid approaches are proposed as solution techniques for the first time. The Taguchi method is used to obtain the best combinations of algorithm parameters. In addition, problem instances are generated to validate the proposed model for a real-world case. Finally, the effectiveness of the algorithms is compared by using different criteria.