Voyage Segmentation and Propulsive Power Allocation: A Data-Driven Approach for Short Sea Shipping

Licentiate thesis, 2025

Short-sea shipping, a sustainable alternative to land-based transport, faces strict environmental regulations and operational constraints to reduce fuel consumption, emissions, and costs. This thesis aims to minimise fuel consumption in short-sea shipping while adhering to sailing time constraints by developing a framework for optimising engine power allocation across predefined maritime routes. To address the limitations of existing power allocation methods, specifically their limited adaptability to metocean conditions, performance accuracy challenges, and long optimisation times, three approaches are examined: (1) Data-driven modelling, (2) Power allocation optimisation, and (3) Route segmentation.
The first part of the research project analyses a double-ended ferry. Here, data mining techniques were used to uncover trends in fuel consumption linked to power allocation of the ferry, revealing potential savings of up to 35% compared to actual operational data. Building on these findings, a decision support system (DSS) was developed, combining XGBoost to model fuel consumption and sailing time with Bayesian optimisation to recommend optimal engine speed and engine load. Full-scale experiments validated the DSS, achieving an average 18% reduction in the vessel’s fuel consumption
through the proposed engine power allocation strategies.
In the second half, the developed data-driven methods were combined with a novel voyage optimisation method performed in two steps. 1) Route segmentation: ship routes were segmented using the metocean score-based pruned exact linear time (MS-PELT) algorithm to identify optimal segments for engine power adjustments; 2) Engine power allocation, a scenario-based analysis grid was generated for each segment, and dynamic programming was used to determine the optimal power allocation for the voyage. The combined approach was tested on three years of data from a chemical tanker. Numerical simulations showed a 14% reduction in fuel consumption compared to measurement data, with sailing time deviations below 1%. This research demonstrates that the proposed framework significantly improves fuel efficiency in short-sea shipping while maintaining time constraints.