Multi-Objective Optimization of Integrated Civilian-Military Scheduling of Medical Supplies for Epidemic Prevention and Control

Abstract

In a large-scale epidemic, such as the novel coronavirus pneumonia (COVID-19), there is huge demand for a variety of medical supplies, such as medical masks, ventilators, and sickbeds. Resources from civilian medical services are often not sufficient for fully satisfying all of these demands. Resources from military medical services, which are normally reserved for military use, can be an effective supplement to these demands. In this paper, we formulate a problem of integrated civilian-military scheduling of medical supplies for epidemic prevention and control, the aim of which is to simultaneously maximize the overall satisfaction rate of the medical supplies and minimize the total scheduling cost, while keeping a minimum ratio of medical supplies reservation for military use. We propose a multi-objective water wave optimization (WWO) algorithm in order to efficiently solve this problem. Computational results on a set of problem instances constructed based on real COVID-19 data demonstrate the effectiveness of the proposed method.

Keywords: civilian-military integration; epidemic prevention and control; medical supplies scheduling; multi-objective optimization; water wave optimization.

Figure 1

Satisfaction rates to the demands of some medical supplies during the peak period of COVID-19 in Wuhan, China.

Figure 2

Comparison of the aggregated objective function values obtained by the six algorithms on the four problem instances. The horizontal axis denotes the weight of supply satisfaction rate, and the vertical axis denotes the aggregated objective function value. (a) Instance 1; (b) Instance 2; (c) Instance 3; (d) Instance 4.

Figure 3

Satisfaction rates that were obtained by the six algorithms as well as a mixed 0–1 integer programming approach [19] (only using civilian medical supplies) on the test instances.