Paper
16 May 2024 Research on optimization of refueling strategy considering liner speed selection
Bangxiong Xu
Author Affiliations +
Proceedings Volume 13160, Fourth International Conference on Smart City Engineering and Public Transportation (SCEPT 2024); 1316003 (2024) https://doi.org/10.1117/12.3030463
Event: 4th International Conference on Smart City Engineering and Public Transportation (SCEPT 2024), 2024, Beijin, China
Abstract
Aiming at the selection of refueling ports, the amount of refueling, and the speed selection faced by ships in container liner transportation, taking into account constraints such as carbon emissions, fuel consumption, vessel tank capacity, speed selection, and arrival time window, a fuel replenishment optimization model considering liner speed selection was established with the goal of minimizing vessel fixed costs, fuel costs, and carbon tax costs. An improved linear approximation method is proposed to transform the model into an equivalent linear programming model to obtain the optimal solution. Finally, using a real case study of a shipping company as an example, this paper analyzes the influence of error precision change, arrival time window and fuel price on the decision-making of shipping companies, verifying the effectiveness and practicality of the model and algorithm constructed in this article. The results show that the new method can effectively improve the efficiency and accuracy of calculations, and reduce the operating costs of shipping companies.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Bangxiong Xu "Research on optimization of refueling strategy considering liner speed selection", Proc. SPIE 13160, Fourth International Conference on Smart City Engineering and Public Transportation (SCEPT 2024), 1316003 (16 May 2024); https://doi.org/10.1117/12.3030463
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Carbon

Transportation

Error analysis

Mathematical optimization

Binary data

Data modeling

Decision making

Back to Top