BERS: Locally Optimal Continuous Algorithm for Maritime Weather Routing with Just-in-Time Arrival

Fuente: arXiv
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Hauptverfasser: Precioso, Daniel, Suárez, Francisco, de la Jara, Javier Jiménez, Ballester-Ripoll, Rafael, Gómez-Ullate, David
Format: Preprint
Veröffentlicht: 2026
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author Precioso, Daniel
Suárez, Francisco
de la Jara, Javier Jiménez
Ballester-Ripoll, Rafael
Gómez-Ullate, David
author_facet Precioso, Daniel
Suárez, Francisco
de la Jara, Javier Jiménez
Ballester-Ripoll, Rafael
Gómez-Ullate, David
contents Maritime weather routing must optimize route geometry under dynamic wind-wave conditions, obstacle constraints, and fixed-arrival requirements. We present Bézier Evolve and Refine Strategy (\name{}), a two-stage framework that combines global evolutionary search (CMA-ES) with local variational refinement (FMS). Routes are parametrized as Bézier curves and evaluated with dense along-path sampling, enabling smooth trajectories while preserving practical feasibility constraints and accounting for mid-segment effects. We evaluate \name{} on synthetic benchmarks designed to stress seven operational criteria: continuity, obstacle avoidance, dynamic adaptation, flexible objective design, constant-load feasibility, just-in-time arrival, and local optimality. Across these tests, \name{} matches or improves published baselines while maintaining robust convergence under challenging flow fields and land geometries. We then validate the method on real ocean data using hourly ERA5 forcing over 366 daily departures in 2024 for two trans-oceanic corridors (Atlantic and Pacific), with a physics-based model of an 88~m cargo vessel with optional rigid wingsails. In real-ocean experiments, route optimization alone reduces mean propulsive energy by 23--59\% versus great-circle baselines of the same propulsion mode. Combined with wind-assisted propulsion, total savings reach up to 75\%. These results show that \name{} provides a practical and scalable foundation for just-in-time, energy-efficient weather routing in maritime decarbonization workflows.
format Preprint
id arxiv_https___arxiv_org_abs_2605_31533
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle BERS: Locally Optimal Continuous Algorithm for Maritime Weather Routing with Just-in-Time Arrival
Precioso, Daniel
Suárez, Francisco
de la Jara, Javier Jiménez
Ballester-Ripoll, Rafael
Gómez-Ullate, David
Emerging Technologies
Optimization and Control
Maritime weather routing must optimize route geometry under dynamic wind-wave conditions, obstacle constraints, and fixed-arrival requirements. We present Bézier Evolve and Refine Strategy (\name{}), a two-stage framework that combines global evolutionary search (CMA-ES) with local variational refinement (FMS). Routes are parametrized as Bézier curves and evaluated with dense along-path sampling, enabling smooth trajectories while preserving practical feasibility constraints and accounting for mid-segment effects. We evaluate \name{} on synthetic benchmarks designed to stress seven operational criteria: continuity, obstacle avoidance, dynamic adaptation, flexible objective design, constant-load feasibility, just-in-time arrival, and local optimality. Across these tests, \name{} matches or improves published baselines while maintaining robust convergence under challenging flow fields and land geometries. We then validate the method on real ocean data using hourly ERA5 forcing over 366 daily departures in 2024 for two trans-oceanic corridors (Atlantic and Pacific), with a physics-based model of an 88~m cargo vessel with optional rigid wingsails. In real-ocean experiments, route optimization alone reduces mean propulsive energy by 23--59\% versus great-circle baselines of the same propulsion mode. Combined with wind-assisted propulsion, total savings reach up to 75\%. These results show that \name{} provides a practical and scalable foundation for just-in-time, energy-efficient weather routing in maritime decarbonization workflows.
title BERS: Locally Optimal Continuous Algorithm for Maritime Weather Routing with Just-in-Time Arrival
topic Emerging Technologies
Optimization and Control
url https://arxiv.org/abs/2605.31533