MetaGradient driven strategy decomposition for accelerated equilibrium in large scale logistics networks

Dandan Wang and Ni Sun

PLOS ONE, 2025, vol. 20, issue 11, 1-23

Abstract: Static models fail to track the fast-changing supply-demand balance in global logistics. For instance, the high-speed rail express corridor exhibits a transport capacity utilisation rate of less than 70% during peak periods, along with a node load imbalance of 0.57. Existing algorithms have been shown to exhibit a 7.8% prediction error and 38% convergence time overruns during sudden demand changes. This study proposes a gradient-driven framework that combines sparse gradient, tensor decomposition, and constrained multi-objective optimization. Cost drops 28.3%, transit time shrinks 37.3%, container turnover rises 41.4%, and CO₂ falls 27.7%. In the 15-node network, the framework achieves a capacity matching degree of 89.3% with a root mean square error of 0.145, which is better than the benchmark performance of traditional methods and reinforcement learning methods. This research innovates a scalable real-time optimization paradigm, realizes sub-second equilibrium convergence and anti-disturbance recovery of large-scale logistics networks, and lays a foundation for intelligent, low-carbon and resilient logistics ecology.

Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0332537 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 32537&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0332537

DOI: 10.1371/journal.pone.0332537

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().