modeling and solving a four-echelon supply chain network under disruption by multi-objective meta-heuristic algorithms

Supply chain complexity and disintegration lead to increased uncertainty from a stakeholders’ perspective, which is emerging as one of the major challenges of disruption management. the ability to identify disruption possibility has weakened, as the responsibility of supply chain risk management is handed over to outside service providers. regardless, the disruption, their visibility and their impact depend on the position of the companies in the supply chain. the actors in the chain must therefore collaborate to create effective risk management conditions. this work develops a multi-objective programming model for a multi-echelon, multi-product, multi-period supply chain planning under disruption. this model includes minimizing total purchase, transportation, shortage and holding cost, also maximizing total score of each one. the proposed model is solved in two multi-objective meta- heuristic algorithms and the results are investigated then results are analysed by comparative criteria. the reason for the use of meta-heuristic algorithms is the np-hard of the proposed model.