Design of Multi-Objective Model for Disruption Risk Assessment of Supply Chain Using Combined Genetic Algorithm and Simulated Annealing

Due to the many risks involved in the supply chain, and the high costs associated with damage to the supply chain, risk identification and evaluation should be a top priority in risk management programs in organizations. Risk assessment and ratings determine the superiority of each risk based on the relevant indicators and thus provide an appropriate response to each risk. In this regard, this research has been addressed a two-objective mathematical model with a multi-source supply policy and lateral transshipment approach to the assessment of the risk of supply chain disruptions. A mathematical model, with emphasis on cost reduction and shortage value, is designed by considering the disturbance parameter on the chain. The model is solved using meta-heuristic algorithms, genetic algorithm and simulated annealing.. Next, we investigate the impact of four disturbances on the costs of the supply chain and the disruptions are evaluated and ranked based on the costs involved in the chain. The results showed that disruption of natural disasters was recognized as the most critical disruption. The findings indicate that the proposed approach is an effective framework for identifying effective parameters and prioritizing the risk of supply chain disruptions.