Designing a Scenario-Based Fuzzy Model for Sustainable Closed-Loop Supply Chain Network considering Statistical Reliability: A New Hybrid Metaheuristic Algorithm

In this study, a new nonlinear mathematical programming model of mixed integer was presented to formulate the problem designing sustainable closed loop supply chain, in which three aspects sustainability, i.e., social effect such as job creation, customer satisfaction, and distributors, environmental effects reducing air pollution, economic chain costs, increasing reliability, quality returned products by customers, product routing were considered. order solve proposed model, hybrid metaheuristic algorithm based on distinctive features gray wolf genetic addition MOPSO NSGA-II algorithms. After tuning their parameters Taguchi method, performance problems with different dimensions tested evaluated MID, DM, SM criteria. The results statistical analysis indices indicated that no significant difference between algorithms at 5% error level. general, GW-NS, had better terms MID index, respectively. addition, NSGA-II, performed DM index. MOPSO, GW-NS variability index all almost same, but algorithm, highest change less sustainability.