Marine Voyage Optimization and Weather Routing with Deep Reinforcement Learning
Marine voyage optimization determines the optimal route and speed to ensure timely arrival. The problem becomes particularly complex when incorporating a dynamic environment, such as future expected weather conditions along the route and unexpected disruptions. This study explores two model-free Dee...
Saved in:
| Main Authors: | Charilaos Latinopoulos, Efstathios Zavvos, Dimitrios Kaklis, Veerle Leemen, Aristides Halatsis |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | Journal of Marine Science and Engineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-1312/13/5/902 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Optimum routing for dry bulk voyages with the effect of an emission trading system: NSR vs SCR
by: Chathumi Ayanthi Kavirathna, et al.
Published: (2025-06-01) -
A Two-Criteria Weather Routing Method Based on Neural Network and A-star Algorithm
by: Khanh Huu Doan, et al.
Published: (2024-05-01) -
Anomalous Behavior in Weather Forecast Uncertainty: Implications for Ship Weather Routing
by: Marijana Marjanović, et al.
Published: (2025-06-01) -
Entre itinéraires et trajets : représentations des déplacements dans les guides de voyage au tournant du XIXe siècle
by: Ariane Devanthéry
Published: (2011-06-01) -
The Application of a Marine Weather Data Reconstruction Model Based on Deep Super-Resolution in Ship Route Optimization
by: Shangfu Li, et al.
Published: (2025-05-01)