Development of a novel forward dynamic programming method for weather routing

Shao, Wei; Zhou, Peilin; Thong, Sew Kait

doi:10.1007/s00773-011-0152-z

Cited by 127 publications

(54 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Dijkstra's algorithm was used to determine the minimum energy path for a surface ship [9], and the Theta* algorithm, which is a modified version of A*, was applied to path planning [10]. Wind and waves were also considered under the name of weather routing in [11][12][13][14]. These researches considered the added resistance induced by wind and waves for the path planning and the paths were generated using conventional methods such as A* and dynamic programming.…”

Section: Related Workmentioning

confidence: 99%

Path optimization for marine vehicles in ocean currents using reinforcement learning

Yoo

Kim

2015

J Mar Sci Technol

View full text Add to dashboard Cite

This study proposes a path planning algorithm for marine vehicles based on machine learning. The algorithm considers the dynamic characteristics of the vehicle and disturbance effects in ocean environments. The movements of marine vehicles are influenced by various physical disturbances in ocean environments, such as wind, waves, and currents. In the present study, the effects of ocean currents are the primary consideration. A kinematic model is used to incorporate the nonholonomic motion characteristics of a marine vehicle, and the reinforcement learning algorithm is used for path optimization to generate a feasible path that can be tracked by the vehicle. The proposed approach determines a near-optimal path that connects the start and goal points with a reasonable computational cost when the map and current field data are provided. To verify the optimality and validity of the proposed algorithm, a set of simulations were performed in simulated and actual ocean current conditions, and their results are presented.

show abstract

Section: Related Workmentioning

confidence: 99%

Path optimization for marine vehicles in ocean currents using reinforcement learning

Yoo

Kim

2015

J Mar Sci Technol

View full text Add to dashboard Cite

show abstract

“…the calculus of variations [17], the modified isochrone method [18,19], the isopone method [20,21], the two-dimensional dynamic programming [13,22] and the three-dimensional dynamic programming [2]. Apart from above-mentioned algorithms, many other approaches have also been applied to solve these problems, such as the iterative dynamic programming [23], the augmented Lagrange multiplier [24], the Dijkstra algorithm [15,25] and the genetic algorithm [26].…”

Section: Introductionmentioning

confidence: 99%

“…It is well known that the ship routing optimization for oceangoing vessels is widely applied, and a considerable number of studies have been carried out [1][2][3][4][5][6][7][8][9][10]. Typically, ship routing can be modeled as a minimum fuel consumption problem subject to some constraints, which is solved with an optimization method [11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

The optimization of ship weather-routing algorithm based on the composite influence of multi-dynamic elements (II): Optimized routings

Fang

Lin

2015

Applied Ocean Research

View full text Add to dashboard Cite

“…Speed, loading and heading should all be integrated into routing optimization, making the problem multi-dimensional [21].…”

Section: Introductionmentioning

confidence: 99%

The influence of route choice and operating conditions on fuel consumption and CO2 emission of ships

et al. 2016

View full text Add to dashboard Cite

The influence of various parameters, such as ship initial speed (full ahead and lower engine loads), loading condition, heading angle and weather conditions on ship fuel consumption and CO2 emission is presented. A reliable methodology for estimating the attainable ship speed, fuel consumption and CO2 emission in different sea states is described. The speed loss is calculated by taking into account the engine and propeller performance in actual seas as well as the mass inertia of the ship. The attainable ship speed is obtained as time series. Correlation of speed loss with sea states allows predictions of propulsive performance in actual seas. If the computation is used for weather routing purposes, values for various ship initial speed, loading conditions and heading angles for each realistic sea-state must be provided. The voluntary speed loss is taken into account. The influence of the ship speed loss on various parameters such as fuel consumption and CO2 emissions is presented. To illustrate the presented concept, the ship speed and CO2 emissions in various routes of the Atlantic Ocean are calculated using representative environmental design data for the track of the routes where the ship will sail.

show abstract

Development of a novel forward dynamic programming method for weather routing

Cited by 127 publications

References 7 publications

Path optimization for marine vehicles in ocean currents using reinforcement learning

Path optimization for marine vehicles in ocean currents using reinforcement learning

The optimization of ship weather-routing algorithm based on the composite influence of multi-dynamic elements (II): Optimized routings

The influence of route choice and operating conditions on fuel consumption and CO2 emission of ships

Contact Info

Product

Resources

About