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Robust Optimization of Transport Organization for China Railway Express

Authors :
Changjiang Zheng
Yang Shen
Junze Ma
Ling Gui
Chen Zhang
Source :
Applied Sciences, Vol 14, Iss 1, p 137 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

This paper presents an in-depth analysis of the robust optimization of the China–Europe freight train transportation organization under uncertain cargo transportation demand. The study commences by constructing a robust optimization model tailored for specific environments, which is further extended to address the complexities of uncertain freight demand. A notable aspect of this research is the adoption of an innovative approach to manage the uncertainties in freight transportation demand at each node, employing a box-type uncertainty set distribution. This methodology allows for an effective and balanced optimization strategy that accommodates the dynamic nature of demand fluctuations. The research findings underscore that increased robustness in the optimization model is associated with higher transportation costs within the China–Europe freight train network, especially under conditions of variable demand. The model demonstrates a preference for adjusting transportation costs to maintain the stability of the transportation scheme, particularly in response to wider variations in cargo demand. This strategy, prioritizing cost-effectiveness and adaptability, highlights the importance of a comprehensive approach to managing demand uncertainties. The significant contributions of this paper include the development of a robust, economically viable, and efficient transportation organization plan for China–Europe freight trains, equipped to navigate the challenges posed by uncertain cargo demand at the originating nodes. The study’s emphasis on the practical application of advanced optimization techniques and uncertainty management methods marks a notable advancement in the field of freight train transportation. Additionally, the paper suggests avenues for further research in the intricate and evolving landscape of freight transportation, providing valuable insights for future studies.

Details

Language :
English
ISSN :
20763417
Volume :
14
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.555de66b55824ccd9607c75f169d99c6
Document Type :
article
Full Text :
https://doi.org/10.3390/app14010137