Medical supplies scheduling in major public health emergencies.

In the early days of the COVID-19 pandemic in Wuhan, there was an unreasonable allocation between hospitals and a lack of timely transportation of medical supplies, which reduced the cure rate of infected cases. To solve the problem, this research proposes a method for scheduling medical supplies in major public health emergencies to develop a rapid and accurate supply scheme for medical materials, including the allocation of medical materials per vehicle to each hospital and the supply sequence per vehicle to each hospital. Specifically, this paper solves the following two sub-problems: (1) calculating the shortest transportation times and the corresponding routes from any distributing center(s) to any hospital(s); (2) calculating the medical supplies per vehicle transporting to each hospital. The method of solving sub-problem 1 is performed by multiple iterations, each of which calculates the shortest route from a distributing center, through one or more hospitals, and back to the distributing center. According to sub-problem 2, this research proposes a distribution model of medical supplies in major public health emergencies. A multiple dynamic programming algorithm which is a combination of some separated dynamic programming operations is proposed to solve this model. This algorithm also realizes the rapid updating of the scheme in the context of the changing number of vehicles. The first sub-problem can be solved in normal times, while the second one should be solved on the premise of obtaining the corresponding data after the occurrence of a major public health emergency. In the case study section, the whole method proposed in this research is employed in the medical supplies scheduling in the early stage of the COVID-19 outbreak in Wuhan, which proves the availability of the method. The main innovation of the method proposed in this research is that the problems can obtain the optimal solution while the time complexity is within an acceptable range.