A Novel Virtual Arrival Optimization Method for Traffic Organization Scenarios

Tianhao Shao, Weijie Du, Yun Ye, Haoqing Li, Jingxin Dong, Guiyun Liu () and Pengjun Zheng ()
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Tianhao Shao: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
Weijie Du: Ningbo Pilot Station, Ningbo 315040, China
Yun Ye: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
Haoqing Li: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
Jingxin Dong: Business School, Newcastle University, Newcastle upon Tyne NE1 ASE, UK
Guiyun Liu: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
Pengjun Zheng: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China

Sustainability, 2024, vol. 16, issue 1, 1-17

Abstract: The International Maritime Organization (IMO) has been progressively implementing stricter regulations on ship carbon emissions, leading to many vessels adopting the virtual arrival (VA) method to reduce their carbon footprint. However, the effectiveness of the traditional VA method often varies in busy ports with complex traffic organization scenarios. To address this, our study presents a novel, comprehensive model that integrates vessel scheduling with the VA approach. This model is designed to achieve a dual objective: reducing carbon emissions through virtual arrival while simultaneously minimizing vessel waiting times. In addition to these goals, it incorporates essential aspects of safety, efficiency, and fairness in port management, utilizing the NSGA-2 algorithm to find optimal solutions. This model has been tested and validated through a case study at Ningbo-Zhoushan port, employing its dataset. The results demonstrate that our innovative model and algorithm significantly outperform traditional scheduling methods, such as First-Come-First-Serve (FCFS) and Virtual-Arrival Last-Serve (VALS), particularly in terms of operational efficiency and reduction in vessel carbon emissions.

Keywords: virtual arrival; traffic organization; carbon emission reduction; waiting time; multi-objective optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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