Research on emergency logistics information traceability model and resource optimization allocation strategies based on consortium blockchain

Chuansheng Wang, Zixian Guo, Fulei Shi, Mingyue Chen, Xinyu Wang and Jia Liu

PLOS ONE, 2024, vol. 19, issue 5, 1-17

Abstract: In response to increasingly complex social emergencies, this study realizes the optimization of logistics information flow and resource allocation by constructing the Emergency logistics information Traceability model (ELITM-CBT) based on alliance blockchain technology. Using the decentralized, data immutable and transparent characteristics of alliance blockchain technology, this research breaks through the limitations of traditional emergency logistics models and improves the accuracy and efficiency of information management. Combined with the hybrid genetic simulated Annealing algorithm (HGASA), the improved model shows significant advantages in emergency logistics scenarios, especially in terms of total transportation time, total cost, and fairness of resource allocation. The simulation results verify the high efficiency of the model in terms of timeliness of emergency response and accuracy of resource allocation, and provide innovative theoretical support and practical scheme for the field of emergency logistics. Future research will explore more efficient consensus mechanisms, and combine big data and artificial intelligence technology to further improve the performance and adaptability of emergency logistics systems.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0303143

DOI: 10.1371/journal.pone.0303143

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