Dynamic Transit Scheduling of Medical Goods in Regular Operations

Currently, medical goods transit plans are usually made by staff with experience, without optimization from a systemic perspective. As a result, feasible but inferior decisions have usually been made. Therefore, in this research, based on a medical institution's perspective, we consider the demand of goods for every time slot in all hospital departments, the stock capacity and other constraints, and then employ the time-space network techniques to construct a medical goods transit scheduling model, as well as a dynamic decision framework, to help the medical institutions efficiently schedule their medical goods transshipments in regular operations. Finally, we perform a case study based on a domestic large-scale medical institution's operating data. The preliminary results are good, showing that the model and the dynamic decision framework could be useful references for medical systems.