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Author: Daniel Precioso

_posts/2023-10-06-hybrid-search.md

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 During the past few months we have been collaborating with Dalhousie University in implementing a novel method to weather routing. We named it the "Hybrid Search" algorithm and aims to tackle the Zermelo's Navigation Problem. Today, the most recent version of the paper explaining this approach has been uploaded to ArXiV!
 
-[**Download the full paper here**]({{ page.paperurl }})
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 Our Hybrid Search method can be regarded as an extension of the recent Ferraro-Martín de Diego-Almagro to allow for further exploration in search for the global optimum, in situations of complex vector fields where many locally optimal trajectories exist. Our algorithm is designed to work in both Euclidean and spherical spaces and utilizes a heuristic that allows the vessel to move forward while remaining within a predetermined search cone centred around the destination. This approach not only improves efficiency but also includes obstacle avoidance, making it well-suited for real-world applications. We evaluate the performance of the HS algorithm on synthetic vector fields and real ocean currents, demonstrating its effectiveness and performance.
 
 <img src="{{ page.featured_image }}" alt="Hybrid Search" width="100%"/>
 
+<a href="https://doi.org/10.48550/arXiv.2308.02434" class="button">Download the full paper here</a>
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 This research on weather routing is possible thanks to the research grant from [BBVA Foundation](https://www.fbbva.es/) and [Agencia Estatal de Investigación](https://www.aei.gob.es/). All researchers involved in this project want to express their gratitude towards them.
 
 At this very moment, the paper is under review. We hope to share updates soon about its publication. Stay tuned!