Abstract

Shipping significantly contributes to air pollution and greenhouse gas emissions, accounting for more than 80% of global trade. Consequently, governments have been focused on air pollution reduction for many years. The adoption of shore power systems has increased, recognized for their effectiveness in reducing emissions. This study introduces multi-objective mixed-integer programming models to investigate the impacts of government-subsidy-based and berthing-priority-based incentive policies on various types of expense benefits from the perspectives of different stakeholders. This paper aims to optimize shore power equipment deployment, berth allocation, and ship scheduling while balancing environmental benefits, costs associated with shore power, and operational efficiency. We design an improved NSGA-II with a two-stage solution algorithm to solve the studied problem, which is more suitable for large-scale case calculations. Following the case study, we offer insights for stakeholders to navigate the complexities of sustainable port development and promote the adoption of shore power systems.

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