Sustainable and reliable closed-loop supply chain network design during pandemic outbreaks and disruptions

This paper aims to design a mathematical model for sustainable closed-loop supply chains during the coronavirus (COVID-19) outbreak. The proposed multi-objective minimizes total cost, carbon emission, and infection risk of network also maximizes social benefits. Some practical conditions such as stochastic demands, supplier selection, facility disruptions are considered in model. is transformed into deterministic by Chance-Constrained Programming (CCP) approach. Thirty test datasets applied examine effects COVID-19 on performance network. problems solved under two (with without considerations), results show that inventory with higher than COVID-19. Moreover, value aggregated objectives greater other which indicates distance from optimal objectives. However, computational efficiency much one. sensitivity analyses carried out, several policy implications proposed. According demand analysis, when managers expect demands will increase, they should focus objective. On contrary, decreased pay more attention environmental economic analysis objectives’ weights investing dimensions needs financial resources compared dimension.