HADAD news post

Author: Daniel Precioso

_posts/2025-01-01-hadad.md

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+---
+title: "New Publication in Ocean Engineering"
+date: 2025-01-01
+permalink: /news/2025/hadad
+excerpt: "Announcing our new paper presenting the HADAD algorithm for advanced weather routing."
+featured_image: "https://weathernavigation.com/images/2025-01-01-hadad.jpeg"
+tags:
+  - weather routing
+  - optimization
+  - naval engineering
+  - ocean engineering
+  - elsevier
+  - publication
+  - journal
+---
+
+We are thrilled to kick off 2025 by announcing our newest scientific contribution. Our team has just published the paper "HADAD: Hexagonal A-Star with Differential Algorithm Designed for weather routing" in the journal of Ocean Engineering.
+
+Weather Navigation focuses on developing cutting-edge optimization methods to address the challenges of weather routing. In this publication, we introduce HADAD (Hexagonal A-Star with Differential Algorithm Designed for weather routing), a novel approach that first applies an A* search on a hexagonal grid with extended neighbor relationships, allowing more directional flexibility than standard graph-based searches. This global exploration is then refined by a discrete Newton–Jacobi variational technique, guaranteeing convergence to a locally optimal, smoothly curved path in continuous space.
+
+<img src="{{ page.featured_image }}" alt="Hybrid Search" width="100%"/>
+
+To assess HADAD's performance, we compiled a comprehensive benchmark of 1,560 test scenarios covering an entire year, featuring diverse origin-destination pairs, vessel speeds, and environmental conditions. Our findings indicate that HADAD provides an additional 4% improvement over pure A* graph methods compared to the shortest-distance route, thanks to its flexible, gradient-based refinements. A seasonal analysis reveals markedly higher gains in winter, sometimes doubling those in summer, with savings peaking at 27% under extreme weather. Additionally, testing the algorithm with synthetic vector fields demonstrated its adaptability for fuel consumption optimization and Just-in-Time arrivals.
+
+<a href="https://doi.org/10.1016/j.oceaneng.2024.120050" class="button">Read the new paper here</a>
+
+This research is supported by:
+
+- [BBVA Foundation](https://www.fbbva.es/) via the project "Mathematical optimization for a more efficient, safer and decarbonized maritime transport".
+
+- Spanish [Agencia Estatal de Investigación](https://www.aei.gob.es/) under grant  TED2021-129455B-I00, "Optimization of maritime routes with real time oceanographic and meteorological data".