Ship weather routing using pathfinding algorithms: the case of Barcelona – Palma de Mallorca

Grifoll, Manel; Martorell, L.; Castells, Marcel.la; Osés, Francesc Xavier Martínez de

doi:10.1016/j.trpro.2018.10.106

Cited by 19 publications

(14 citation statements)

References 7 publications

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“…In general, the navigation uncertainty forecasting includes pre-voyage forecasting and intra-voyage forecasting [30]. Responding to the pre-voyage forecasting navigation uncertainties is widely known as the weather routing problems, or pre-voyage planning [30][31][32]. But the conventional ships are rather difficult to respond to the intra-voyage navigation uncertainties, since in conventional ships, the prime motors are connected with propellers via shafts and gearboxes, and the speed regulation ability of conventional ships are therefore limited.…”

Section: Energy Storage Management In Aes For Navigation Uncertaintiesmentioning

confidence: 99%

Energy Storage Management of Maritime Grids

Fang

Wang

2021

Optimization-Based Energy Management for Multi-Energy Maritime Grids

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Section: Energy Storage Management In Aes For Navigation Uncertaintiesmentioning

confidence: 99%

Energy Storage Management of Maritime Grids

Fang

Wang

2021

Optimization-Based Energy Management for Multi-Energy Maritime Grids

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“…Route planning is an important feature of the ship's onboard control system. The crew uses this feature to plot efficient routes taking into account weather conditions, legal regulations, fuel efficiency and other requirements [17]. If the system fails to plot an effective route or the resulting route is not suitable for some reason, the crew still can intervene and introduce corrections.…”

Section: Autonomous Navigationmentioning

confidence: 99%

“…Taking the weather into account not only helps to avoid negative effects on the ship [35,41] but also reduces the economical costs of a voyage by reducing the travel time and fuel consumption [16,43]. Therefore, the ability to take weather conditions into account is essential for the route planning system [17,23,38].…”

Section: Autonomous Navigationmentioning

confidence: 99%

“…It is possible to tune the algorithm to take into account requirements specific for a particular task, e.g. weather conditions [17], ice [45] or in order to reduce the computation time [28]. However, A* is known to be highly dependant on the heuristic function used to determine which vertices to investigate and for its high memory consumption in case of the large search spaces (grid with many vertices) [33].…”

Section: Autonomous Navigationmentioning

confidence: 99%

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Towards Autonomous Shipping: Benefits and Challenges in the Field of Information Technology and Telecommunication

Yanchin¹,

Petrov²

2020

TransNav

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This paper is dedicated to an overview of components of an onboard control system of an autonomous ship. This system controls and operates the ship. Therefore, this system needs to be able to analyze the ship's state, predict its future development and analyze the consequences of its own decisions. The paper focuses on software aspects of the onboard control system, not the hardware. The paper provides an overview of technologies that can be used to implement the components of such a system responsible for planning new routes, handling the ship during the voyage, ensuring its seaworthiness and safety during the voyage, monitoring an autonomous ship from an onshore control centre, ensuring the robustness of the onboard control system, and collective operations of multiple autonomous ships. The paper describes benefits the maritime industry would gain from deploying some of the technologies developed for autonomous ships on ordinary, human-controlled ships. The paper also describes some challenges, especially in the field of automatic decision and reasoning, arising from the emergence of autonomous and smart ships. The main contribution of the paper is that it summarizes existing research in different areas of autonomous ship technology.

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“…These studies present methods that optimise a ship's route from port A to port B, and may or may not take speed profile optimisation into account. Used methods include the isochrone method and its variants [11][12][13], various dynamic programming approaches including forward dynamic programming [14,15], path-finding algorithms [16,17], and the Bellman-Ford algorithm [18], and methods that employ a non-linear solver, such as a genetic algorithm, to solve the voyage optimisation problem [19]. These methods were originally developed to solve the problem of routing only, assuming a fixed speed for the vessel.…”

Section: Introductionmentioning

confidence: 99%

Convex Optimisation Model for Ship Speed Profile: Optimisation under Fixed Schedule

Huotari

Manderbacka

Ritari

et al. 2021

JMSE

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We present a novel convex optimisation model for ship speed profile optimisation under varying environmental conditions, with a fixed schedule for the journey. To demonstrate the efficacy of the proposed method, a combined speed profile optimisation model was developed that employed an existing dynamic programming approach, along the novel convex optimisation model. The proposed model was tested with 5 different ships for 20 journeys from Houston, Texas to London Gateway, with differing environmental conditions, which were retrieved from actual weather forecasts. As a result, it was shown that the combined model with both dynamic programming and convex optimisation was approximately 22% more effective in developing a fuel saving speed profile compared to dynamic programming alone. Overall, average fuel savings for the studied voyages with speed profile optimisation was approximately 1.1% compared to operation with a fixed speed and 3.5% for voyages where significant variance in environmental conditions was present. Speed profile optimisation was found to be especially beneficial in cases where detrimental environmental conditions could be avoided with minor speed adjustments. Relaxation of the fixed schedule constraint likely leads to larger savings but makes comparison virtually impossible as a lower speed leads to lower propulsion energy needed.

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Ship weather routing using pathfinding algorithms: the case of Barcelona – Palma de Mallorca

Cited by 19 publications

References 7 publications

Energy Storage Management of Maritime Grids

Energy Storage Management of Maritime Grids

Towards Autonomous Shipping: Benefits and Challenges in the Field of Information Technology and Telecommunication

Convex Optimisation Model for Ship Speed Profile: Optimisation under Fixed Schedule

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