Research on Optimization and Intelligent Upgrading Strategies for Emergency Logistics Systems

Qi Liu (), Jun Liu (), Yifan Yang () and Yafei Wang ()
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Qi Liu: Logistics Support Academy of the People’s Armed Police
Jun Liu: Logistics Support Academy of the People’s Armed Police
Yifan Yang: Logistics Support Academy of the People’s Armed Police
Yafei Wang: Logistics Support Academy of the People’s Armed Police

A chapter in Proceedings of the 2024 6th Management Science Informatization and Economic Innovation Development Conference (MSIEID 2024), 2025, pp 605-612 from Springer

Abstract: Abstract This paper aims to explore the optimization and intelligent upgrading strategies for emergency logistics systems, proposing a series of innovative methods from the perspective of supply chain management to enhance the response speed and efficiency of emergency logistics. With the frequent occurrence of global emergencies such as natural disasters and public health crises, the importance of emergency logistics has become increasingly prominent. By analyzing the characteristics and challenges of emergency logistics and incorporating modern technologies like artificial intelligence, big data, and the Internet of Things (IoT), this paper presents a systematic set of optimization strategies aimed at building a more flexible and efficient emergency logistics system.

Keywords: Emergency Logistics; Supply Chain Optimization; Intelligent Upgrading; Big Data; Internet of Things (search for similar items in EconPapers)
Date: 2025
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DOI: 10.2991/978-94-6463-676-5_59

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