Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/107812
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Title: Managing port disruption through sailing speed optimization for sustainable maritime transportation
Authors: Guo, S
Wang, H 
Wang, S 
Issue Date: Jun-2024
Source: Cleaner logistics and supply chain, June 2024, v. 11, 100153
Abstract: Ports, as nodes in maritime transportation, frequently face disruptions leading to congestion, adversely affecting the efficiency and sustainability of the global supply chain. This study considers the speeding-up strategy to alleviate port congestion. We model the transportation network as a closed Jackson network and adopt a tailored mean-value analysis algorithm to solve the model. To deliver the increased sailing speed, we further put forward a bi-section search algorithm. Our numerical analysis results demonstrate the feasibility of increasing speed to alleviate port congestion. However, when port congestion exceeds a certain threshold, the system faces collapse, rendering the increase in speed ineffective. Additionally, we recommend shipping companies consider using clean energy when employing the speeding-up strategy to mitigate congestion, thus safeguarding the environment. Our study combines theoretical methodologies and analytical models, providing insights regarding speeding up the vessels. The findings of this study offer guidelines for real-world sustainable maritime practice.
Keywords: Disruptions
Green shipping
Port congestion
Port management
Ship sailing speed
Publisher: Elsevier BV
Journal: Cleaner logistics and supply chain 
EISSN: 2772-3909
DOI: 10.1016/j.clscn.2024.100153
Rights: © 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
The following publication Guo, S., Wang, H., & Wang, S. (2024). Managing port disruption through sailing speed optimization for sustainable maritime transportation. Cleaner Logistics and Supply Chain, 11, 100153 is available at https://doi.org/10.1016/j.clscn.2024.100153.
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