Optimizing Coordinative Schedules for Tanker Terminals: An Intelligent Large Spatial-Temporal Data-Driven Approach -- Part 2

• URL: http://arxiv.org/abs/2204.03955v1
• Date: Fri, 8 Apr 2022 09:30:23 GMT
• Title: Optimizing Coordinative Schedules for Tanker Terminals: An Intelligent Large Spatial-Temporal Data-Driven Approach -- Part 2
• Authors: Deqing Zhai and Xiuju Fu and Xiao Feng Yin and Haiyan Xu and Wanbing Zhang and Ning Li
• Abstract summary: A novel coordinative scheduling optimization approach is proposed to enhance port efficiency by reducing turnaround time. The experimental results show that the proposed approach is effective and promising on mitigating the turnaround time of vessels.
• Score: 4.181498820782148
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: In this study, a novel coordinative scheduling optimization approach is proposed to enhance port efficiency by reducing weighted average turnaround time. The proposed approach is developed as a heuristic algorithm applied and investigated through different observation windows with weekly rolling horizon paradigm method. The experimental results show that the proposed approach is effective and promising on mitigating the turnaround time of vessels. The results demonstrate that largest potential savings of turnaround time (weighted average) are around 17 hours (28%) reduction on baseline of 1-week observation, 45 hours (37%) reduction on baseline of 2-week observation and 70 hours (40%) reduction on baseline of 3-week observation. Even though the experimental results are based on historical datasets, the results potentially present significant benefits if real-time applications were applied under a quadratic computational complexity.

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