Research on Vehicle Scheduling of Medical Materials under Epidemic Situation Based on Ant Colony Optimization Algorithm

Inhalt:
At present, the outbreak of COVID-19 has seriously affected people's lives and health. The research on medical supplies during the epidemic situation is particularly important. The dispatch of medical supplies under the epidemic is different from ordinary supplies and has its own particularities. Therefore, on the basis of previous research, combined with the characteristics of infectious diseases and prevention and control methods, this study establishes a multi-objective emergency dispatch model for medical supplies that maximizes rescue value, minimizes delay losses, and minimizes transportation costs. It translates into a single-objective programming problem. According to the characteristics of this model, the ant colony algorithm is used to solve it, and it is proved that the ant colony optimization algorithm has a good effect in solving this problem by using an example.