Research on optimization of cross-regional dynamic cooperative emergency logistics location-allocation with patient transfer

Based on the actual needs of cross-regional emergency resource allocation among multiple disaster areas during public health emergencies, this paper investigated the location-allocation problem of cross-regional dynamic cooperative emergency logistics involving patient transfer. A two-stage optimal decision-making model was proposed, addressing the dynamic changes in patients and hospital location in the first stage and the location of emergency logistics centers and the distribution of emergency materials in the second stage. The proposed model considered two optimal objectives. The first optimal objective aimed to minimize the total cost of emergency logistics including fixed and operating costs of facilities, and the second one was to minimize the total transfer time while considering the actual demand for dynamic changes over multiple periods. Based on the characteristics of the multi-period dynamic problem, an improved genetic algorithm embedded model predictive control (MPC) method was designed to solve the cross-regional dynamic cooperative emergency logistics location-allocation problem. The above proposed algorithm included three important steps at each planning period, which is shown as follows. (1) Disease spread prediction. forecasting of the disease development trend at the beginning of each period, (2) Emergency decision-making planning and implementation, formulation and implementation of emergency logistics location-allocation schemes based on forecast data, and (3) Data updating and schemes dynamic adjustment, collection of relevant statistics at the end of the period to support decision planning for the next period. These three steps were iterated until the end of the last period. Finally, the effectiveness of the proposed optimization model and designed algorithm was demonstrated by a corresponding real-world case study on cross-regional emergency resource cooperative allocation in Guizhou Province. The findings indicate that compared to individual regional emergency responses, cross-regional dynamic cooperative emergency response can effectively reduce the total costs of emergency logistics without significantly increasing transport time, while efficiently configuring the emergency facilities to provide treatment for infected patients. This study provided a decision support tool for cooperative configuration and scheduling optimization of cross-regional emergency logistics resources. © 2024, Central South University Press. All rights reserved.