Multi-Agent Optimization Algorithms for Emergency Logistics Networks and Their Applications in Public Health Emergencies

Authors

  • Xiaowei Wu School of Environment and Civil Engineering, Dongguan University of Technology
  • Jun Tian School of Environment and Civil Engineering, Dongguan University of Technology

DOI:

https://doi.org/10.70917/jnic-2025-0001

Abstract

This paper investigates the multi-agent optimization algorithms for emergency logistics networks and their applications in public health emergencies. With the acceleration of urbanization and the increasing frequency of emergencies, the optimization of urban network structures for large-scale emergency rescue resource distribution has become increasingly important. Multi-Agent Systems (MAS), known for their flexibility, robustness, and autonomy, have been widely applied in the research of emergency rescue resource distribution. This study introduces a multi-level coverage function for facility location, establishes a multi-objective stochastic programming model for facility location-allocation without capacity constraints, and designs an optimization solution based on genetic algorithms. Through empirical analysis using the collaborative layout of medical material reserve hubs in 33 towns and districts of Dongguan City as a case study, the effectiveness of the model and algorithm is verified. The results show that the optimized emergency logistics network can achieve efficient and fair resource distribution in public health emergencies while considering cost-effectiveness. This research provides theoretical support and practical guidance for the optimal design of emergency logistics networks.

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Published

2025-07-02

How to Cite

Xiaowei Wu, & Jun Tian. (2025). Multi-Agent Optimization Algorithms for Emergency Logistics Networks and Their Applications in Public Health Emergencies . Journal of Network and Innovative Computing, 13, 1–13. https://doi.org/10.70917/jnic-2025-0001

Issue

Vol. 13 (2025)

Section

Original Article

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