Designing dynamic inventory control model using a hybrid meta-heuristic algorithm to optimize the hospital warehouse in the epidemic Covid 19

Inventory management and order planning in medical centers is very important, especially in the context of epidemic diseases, and can have a significant impact on reducing costs, providing optimal services to patients and meeting the needs of medical staff. The main purpose of this study is to design a time-varying multi-commodity dynamic model for optimal inventory management and planning of consumer goods orders of hospitals in the pandemic of Quaid 19. The study area is the Persian Gulf Hospital in Bushehr. In this study, a particle-genetic swarm optimization algorithm under multiple scenarios has been used to solve the mathematical model. The results showed that the proposed model based on the supply of initial demand, in the type and amount of consumption of different goods, has the ability to minimize costs by considering the limit of warehouse volume under multiple scenarios. Also, the hybrid algorithm has a better performance compared to genetic algorithms and particle swarm optimization.