Ventilator distribution network during pandemic situation: a case study on Indian healthcare system

During the pandemic, the indigenous distribution plan of ventilators has been heightened to fulfil urgent hospital requirements. In this study, we have proposed a Global Ventilator Supply Chain Distribution Network (GVSCDN). The deployment of such a model can reduce deaths caused by ventilator scarcity during a deadly pandemic, as observed globally during COVID-19. To demonstrate and deploy GVSCDN, we formulated a Mixed-Integer Non-Linear Programming model to minimize the Total Delivery Time of ventilator distribution using multimodal transportation. Additionally, the developed model has been solved using the Chemical Reaction Optimization (CRO) algorithm. The applications of the proposed mathematical model have been investigated using real-life COVID-19 data related to all states and union territories of India. The results indicate that the proposed design of GVSCDN effectively works in a pandemic under multiple problem instances. Also, examine the responsiveness of the proposed model under randomly generated instances. Finally, the sensitivity analyses have been accomplished by investigating the impact of the model’s essential parameters, such as loading time, unloading time, and speed of the vehicles.