China Safety Science Journal ›› 2026, Vol. 36 ›› Issue (1): 216-226.doi: 10.16265/j.cnki.issn1003-3033.2026.01.0753

• Disaster Prevention and Mitigation Technology and Engineering • Previous Articles     Next Articles

Multi-modal delivery routing planning of medical supplies for flood disasters considering rescue utility

LIU Changshi1(), LIU Tao2, ZHU Yongjun3,**(), YUE Junyu4, WAN Cheng2, LI Junyu5   

  1. 1 School of Business Administration, Hunan University of Technology and Business, Changsha Hunan 410205, China
    2 School of Intelligent Engineering and Intelligent Manufacturing, Hunan University of Technology and Business, Changsha Hunan 410205, China
    3 School of Accounting, Hunan University of Technology and Business, Changsha Hunan 410205, China
    4 School of Artificial Intelligence and Advanced Computing, Hunan University of Technology and Business, Changsha Hunan 410205, China
    5 School of Business Administration, Southwest University of Finance and Economics, Chengdu Sichuan 611130, China
  • Received:2025-08-12 Revised:2025-11-21 Online:2026-01-28 Published:2026-07-28
  • Contact: ZHU Yongjun

Abstract:

To quantify the rescue effect of medical supplies delivered to demand points at different times, the concept of rescue utility is introduced, and a rescue utility quantification function was constructed based on the time difference of medical supplies arriving at demand points. On this basis, a path planning model for multi-modal distribution of medical supplies in flood disasters was established with the objective of maximizing total rescue utility and minimizing total distribution time. According to the characteristics of the model, a HNSGA-II was designed for solution. Experiments were conducted using multiple types of examples. The results demonstrate that HNSGA-II achieves a 62% and 29% improvement in total rescue utility compared to the traditional Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and the Multi-Objective Artificial Bee Colony Algorithm (MOABCA), respectively. Additionally, the average satisfaction level of material delivery time is enhanced by 13% and 6.1%, respectively. These findings indicate that HNSGA-II significantly improves emergency rescue outcomes, exhibits superior multi-objective optimization capability, and ensures that disaster victims receive timely and effective treatment under emergency conditions.

Key words: rescue utility, flood disaster, medical supplies, multi-mode delivery, routing planning, hybrid non-dominated sorting genetic algorithm-II (HNSGA-II)

CLC Number: