Redesign of a sustainable and resilient closed-loop supply chain network under uncertainty and disruption caused by sanctions and COVID-19

Due to the increased levels of uncertainty in the world today and the expansion of supply chain boundaries, companies have been observed trying to enhance supply chain resilience to deal with disruptions caused by severe disasters. There is, however, a new stimulus for the disorder, something quite similar to what has been witnessed recently. It is a new phenomenon called pandemics such as SARS, Ebola, and Coronaviruses. On the other hand, as a result of the imposition of economic sanctions, there is uncertainty in the decision-making parameters of the supply chains, creating difficulties for them. Iron is a raw material that affects both the industry and economy of a nation and can be turned into a closed-loop network. In the current research, using a multi-objective mathematical model, a closed-loop supply chain of steel is presented under the circumstances of the COVID-19 embargo and pandemic. Existing uncertainties are modelled with a robust optimization approach in an uncertain environment. As part of the analysis, appropriate strategies to increase chain resilience will be identified and evaluated. A case study of an active steel supply chain in Iran has been examined for model validation. This model optimizes final net profit, water, and energy use, emissions, and control of coronavirus emissions. In the present study, a three-objective mathematical model is determined and solved in small dimensions based on modified LP-metric and ε-constraint approaches. Further, based on MOPSO and NSGA-II meta-heuristic methods, the best solution was selected in large dimensions.