Optimizing a Supply Chain Network Using Metaheuristic for Pre and Post Pandemic Scenario

Abstract

During the pandemic, the supply chains got highly disrupted and faced a new challenge to sustain service. We have proposed a mathematical model for managing supply chains in a post pandemic situation, also coined as “new normal”. We are trying to design a model and simulate different scenarios while optimizing the network to thrive and fulfill customer demand. The model has been supported with scenario analysis and illustrative examples a packaged drinking water supply chain. The objective is to minimize the supply chain operating cost with respect to the changes in capacity due to pandemic. The fill-rate has also been recorded as a performance matrix for the chain. Particle Swarm Optimization (PSO) has been used to optimize the objective function. This research will help supply chain practitioners and researchers to design networks and carry out study in risk management for pandemic or other similar outbreaks situations.