Insights

Research, whitepapers, and the math behind the model.

We do not sell black boxes. Our weather routing platform is grounded in published, peer-reviewed methodology and built for transparent voyage optimization - helping shipping teams assess route alternatives, manage weather risk, and identify fuel-efficiency gains without relying on unexplained recommendations. Here are the papers and whitepapers behind it.

Whitepaper 2026 12 min read

Why Resolution Wins

Every weather-routing engine is, at its core, a graph. The geometry of that graph determines whether the routing solution can capture meteorological reality, respect coastal safety margins, and remain computationally tractable. Most providers compromise on at least one. This paper explains how VesselFront's adaptive 20+M-node grid resolves all three — and why the result is structurally what you should be after.

"The geometry of that graph determines whether the routing solution can capture meteorological reality."
Authors VesselFront Research
Grid resolutionWeather routingArchitecture
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Conference Paper · Demo Paper 2026 · 27th IEEE MDM 2026 · 29 June – 2 July, Athens 24 min read

VFWR: Charting the Optimal Voyage

VFWR turns weather routing from a black-box recommendation into a transparent, real-time optimization engine that helps operators choose safer and faster routes with confidence. Validated against historical voyages, it consistently identified shorter-duration routes in seconds — combining marine forecasts, vessel-specific constraints, no-go areas, draft safety, and ECA preferences into one practical decision-support platform.

"From forecast to voyage decision in seconds — with routing logic your operators can actually understand."
Authors Aikaterini Karampasi (VesselFront) , Andreas Kouvaras (VesselFront) , Dimitris Stavropoulos (VesselFront) , Alexander Artikis (University of Piraeus)
Weather routingOptimizationSearch spaceSafetyConstraints
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Conference Paper September 15–16, 2026 · The 9th International Symposium on Ship Operations, Management & Economics (SOME) · 15–16 September, Athens 18 min read

Fuel Oil Consumption Prediction Model for AI Optimisation Platform

Our Fuel Oil Consumption model helps operators make fuel-aware voyage decisions with greater confidence. Built on millions of real telemetry points and fleet reports, it transforms vessel performance, engine, draft, trim, speed, and environmental data into practical fuel intelligence for AI-powered voyage optimization.

"Turn raw vessel data into fuel intelligence that improves voyage, cost, and efficiency decisions."
Authors Andreas Kouvaras (VesselFront) , Dimitris Stavropoulos (VesselFront) , Aikaterini Karampasi (VesselFront) , Constantine Abazis (VesselFront) , Michael Fan (Tsakos Energy Navigation · University of Strathclyde) , George Margelis (Tsakos Shipping and Trading)
Fuel Oil Consumption predictionVessel's Main EngineBig Maritime DataTelemetry DataFleet Reports
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Want to discuss the methodology?

The team behind these papers takes briefings from operators, charterers, and underwriters.