An Ant Colony Algorithm for efficient ship routing

Tsou, Ming-Cheng; Cheng, Heqin

doi:10.2478/pomr-2013-0032

Cited by 55 publications

(23 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Different swarm intelligence methods have been used in various scenarios. For example, Kosmas and Vlachos (2012) used simulated annealing, whereas Tsou and Cheng (2013) proposed ant colony optimization for this task. A number of studies have demonstrated the usage of evolutionary algorithms in different configurations, such as multi-objective evolutionary algorithm (Marie and Courteille 2009;Szłapczynska and Smierzchalski 2009;Vettor and Soares 2016), or realcoded genetic algorithm (Maki et al 2011;Wang et al 2018).…”

Section: Related Workmentioning

confidence: 99%

Extracting Maritime Traffic Networks from AIS Data Using Evolutionary Algorithm

et al. 2020

View full text Add to dashboard Cite

The presented method reconstructs a network (a graph) from AIS data, which reflects vessel traffic and can be used for route planning. The approach consists of three main steps: maneuvering points detection, waypoints discovery, and edge construction. The maneuvering points detection uses the CUSUM method and reduces the amount of data for further processing. The genetic algorithm with spatial partitioning is used for waypoints discovery. Finally, edges connecting these waypoints form the final maritime traffic network. The approach aims at advancing the practice of maritime voyage planning, which is typically done manually by a ship’s navigation officer. The authors demonstrate the results of the implementation using Apache Spark, a popular distributed and parallel computing framework. The method is evaluated by comparing the results with an on-line voyage planning application. The evaluation shows that the approach has the capacity to generate a graph which resembles the real-world maritime traffic network.

show abstract

Section: Related Workmentioning

confidence: 99%

Extracting Maritime Traffic Networks from AIS Data Using Evolutionary Algorithm

et al. 2020

View full text Add to dashboard Cite

show abstract

“…When V w is greater than the critical STW, the ship must be slowed down, which is known as the voluntary speed reduction. In this paper, the following equations are used to calculate the critical STW [50,51]:…”

Section: The Speed Correction Modelmentioning

confidence: 99%

Ship Speed Optimization Considering Ocean Currents to Enhance Environmental Sustainability in Maritime Shipping

et al. 2020

View full text Add to dashboard Cite

Enhancing environmental sustainability in maritime shipping has emerged as an important topic for both firms in shipping-related industries and policy makers. Speed optimization has been proven to be one of the most effective operational measures to achieve this goal, as fuel consumption and greenhouse gas (GHG) emissions of a ship are very sensitive to its sailing speed. Existing research on ship speed optimization does not differentiate speed through water (STW) from speed over ground (SOG) when formulating the fuel consumption function and the sailing time function. Aiming to fill this research gap, we propose a speed optimization model for a fixed ship route to minimize the total fuel consumption over the whole voyage, in which the influence of ocean currents is taken into account. As the difference between STW and SOG is mainly due to ocean currents, the proposed model is capable of distinguishing STW from SOG. Thus, in the proposed model, the ship’s fuel consumption and sailing time can be determined with the correct speed. A case study on a real voyage for an oil products tanker shows that: (a) the average relative error between the estimated SOG and the measured SOG can be reduced from 4.75% to 1.36% across sailing segments, if the influence of ocean currents is taken into account, and (b) the proposed model can enable the selected oil products tanker to save 2.20% of bunker fuel and reduce 26.12 MT of CO2 emissions for a 280-h voyage. The proposed model can be used as a practical and robust decision support tool for voyage planners/managers to reduce the fuel consumption and GHG emissions of a ship.

show abstract

“…In addition to the above methods, some evolutionary heuristic algorithms have been used to solve the ship weather routing problem in recent years, such as the simulated annealing algorithm (Kosmas and Vlachos, 2012), ant colony algorithm (Tsou and Cheng, 2013), genetic algorithm (Maki et al, 2011; Kang et al, 2012), and multi-objective evolutionary algorithm (Marie and Courteille, 2009; Szłapczyńska and Śmierzchalski, 2009; Szlapczynska, 2015; Vettor and Soares, 2016).…”

Section: Summary Of Previous Workmentioning

confidence: 99%

Application of Real-Coded Genetic Algorithm in Ship Weather Routing

Wang

et al. 2018

J. Navigation

View full text Add to dashboard Cite

Solving the problem of ship weather routing has been always a goal of nautical navigation research and has been investigated by many scientists. The operation schedule of an oceangoing ship can be influenced by wave or wind disturbances, which complicate route planning. In this paper, we present a real-coded genetic algorithm to determine the minimum voyage route time for point-to-point problems in a dynamic environment. A fitness assignment method based on an individual's position in the sorted population is presented, which greatly simplifies the calculation of fitness value. A hybrid mutation operator is proposed to enhance the search for the optimal solution and maintain population diversity. Multi-population techniques and an elite retention strategy are employed to increase population diversity and accelerate convergence rates. The effectiveness of the algorithm is demonstrated by numerical simulation experiments.

show abstract

An Ant Colony Algorithm for efficient ship routing

Abstract: ABSTRACT

Cited by 55 publications

References 19 publications

Extracting Maritime Traffic Networks from AIS Data Using Evolutionary Algorithm

Extracting Maritime Traffic Networks from AIS Data Using Evolutionary Algorithm

Ship Speed Optimization Considering Ocean Currents to Enhance Environmental Sustainability in Maritime Shipping

Application of Real-Coded Genetic Algorithm in Ship Weather Routing

Contact Info

Product

Resources

About