The Optimization of Fleet Deployment for Container Liner Shipping under the Carbon Tax and Energy Efficiency Operation Indicator
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10, Issue 4
Abstract
To address the ship allocation issues within container liner routes in the context of enhancing energy efficiency and reducing carbon emissions in ship operations, we formulated a dual-objective mixed-integer nonlinear planning model. The model aims to minimize both the operating cost and the Energy Efficiency Operational Indicator (EEOI) of the container liner fleet. The decision-making variables in the model include ship allocation and ship speed. The solution of the model is obtained using the improved Non-Dominated Sorting Genetic Algorithm II (NSGA-II), which leads to the derivation of an optimal ship allocation issues. We selected three routes for one company for illustrative analysis and performed sensitivity analyses on oil prices and carbon tax rates to validate the model and algorithm. The research findings have the potential to assist shipping companies in achieving energy savings and operational cost reductions.
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Data Availability Statement
All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
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Information & Authors
Information
Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10 • Issue 4 • December 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Mar 9, 2024
Accepted: May 8, 2024
Published online: Aug 5, 2024
Published in print: Dec 1, 2024
Discussion open until: Jan 5, 2025
ASCE Technical Topics:
- Analysis (by type)
- Business management
- Coasts, oceans, ports, and waterways engineering
- Construction engineering
- Construction methods
- Container shipping
- Energy efficiency
- Energy engineering
- Engineering fundamentals
- Financial management
- Freight transportation
- Infrastructure
- Linings
- Practice and Profession
- Sensitivity analysis
- Ships
- Sustainable development
- Taxation
- Transportation engineering
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