Year: 2025
Type: article
Abstract: The transition from the use of heavy fuel oil (HFO) to the use of green fuels (e.g., methanol) for container liner shipping presents a significant challenge for liner shipping system design (LSSD) in terms of achieving emission reductions. While methanol, including both green and gray methanol, offers environmental benefits, its lower energy density introduces operational complexities. Motivated by the aforementioned background, we establish a bi-level programming model. This model integrates liner speed management and bunker fuel management strategies (i.e., bunkering port selection and bunkering amount determination) with traditional network design decision (i.e., fleet deployment, shipping network design, and slot allocation) optimization. Specifically, the upper-level model optimizes the number of liners deployed in the fleet and shipping network structure, whereas the lower-level model coordinates decisions associated with liner sailing speed management, bunker fuel management, and slot allocation. Moreover, we propose an adaptive piecewise linearization approach combined with a genetic algorithm, which can efficiently solve large-scale instances. Sensitivity analyses of fuel types and fuel prices are conducted to demonstrate the effectiveness of the model and algorithm. Overall, our paper offers valuable insights for policymakers in designing customized emission reduction policies to support the green fuel transition in the maritime industry.
DOI: 10.3390/jmse13040709
Authors: Zhaokun Li, Xinke Yu, Jianning Shang, Kang Chen, Xu Xin, Wei Zhang, Shaoqiang Yu
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
Award: G2452729871
OpenAlex ID: W4409103457