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

TL;DR

This paper introduces a heuristic scheduling method for tanker terminal coordination that significantly reduces vessel turnaround times, demonstrating potential for improved port efficiency through a data-driven approach.

Contribution

It presents a novel large spatial-temporal data-driven heuristic algorithm for optimizing tanker terminal schedules, with promising results on reducing turnaround times.

Findings

Up to 40% reduction in weighted average vessel turnaround time.

Effective across different observation window durations.

Potential for real-time application with manageable computational complexity.

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.