The Optimization of Fleet Deployment for Container Liner Shipping under the Carbon Tax and Energy Efficiency Operation Indicator

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.