Determination of an economical shipping route considering the effects of sea state for lower fuel consumption

Roh, Myung-Il

doi:10.2478/ijnaoe-2013-0130

Cited by 46 publications

(17 citation statements)

References 2 publications

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“…Joo et al [4] Townsin-Kwon method All ships Bang and Kwon [5] Townsin-Kwon method All ships Lin et al [7] Polynomial function All ships Vettor and Soares [8] Polynomial function All ships Park et al [9] 2nd order polynomial function All ships Roh [10] ISO 15016:2002 All ships Wei and Zhou [11] ISO 15016:2002 All ships Chen [12] ISO 15016:2002 All ships Eniram [14] Statistical method Specific ships SHI [15] Statistical method Specific ships This study ISO 15016:2015 All ships…”

Section: Methods For Estimating Fuel Oil Consumption Applicationmentioning

confidence: 99%

“…However, the methods have a disadvantage in that their accuracy is low depending on the type and shape of ships. Roh [10], Wei and Zhou [11], and Chen [12] studied weather routing and estimated the fuel oil consumption of ships based on the ISO 15016:2002 method [13]. When estimating the fuel consumption using ISO 15016:2002 [13], calculating additional resistance and estimating the power of a ship are outdated and do not reflect recently developed ships and accumulated operating data.…”

Section: Literature Reviewsmentioning

confidence: 99%

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ISO 15016:2015-Based Method for Estimating the Fuel Oil Consumption of a Ship

Kim

Roh

2020

JMSE

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Recently, interest in the design and construction of smart ships has been widely increasing. Optimal route planning is a widely studied essential aspect of smart ship technology. Planning an optimal route requires an accurate estimation of the fuel oil consumption of a ship. Various studies have suggested methods for theoretically estimating the fuel oil consumption. However, the calculation methodology and accuracy are different for each method. In addition, in commercial software, a statistical model based mainly on operating data has been used. Therefore, in this study, we propose a method based on ISO 15016:2015 for estimating the fuel oil consumption of a ship by improving the ISO 15016:2002 method—which has been predominantly used in existing studies. Moreover, the accuracy of the proposed method is examined by comparing it with a gray box model based on operating data. The results confirm that the proposed method can be used for estimating the fuel oil consumption of a ship.

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Section: Methods For Estimating Fuel Oil Consumption Applicationmentioning

confidence: 99%

Section: Literature Reviewsmentioning

confidence: 99%

ISO 15016:2015-Based Method for Estimating the Fuel Oil Consumption of a Ship

Kim

Roh

2020

JMSE

Self Cite

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“…Over the years, various assessments have been carried out of the economic costs and benefits related to the collection and distribution of marine data for ocean research and operational purposes (e.g. OECD (2019 [1]), Rayner, Jolly and Gouldman (2019 [6]), Weller et al (2019[7]), Commonwealth of Australia (2019 [8]), Metz et al (2018[9]), Cristini et al (2016[10]), Kite-Powell, Colgan and Weiher (2008 [11]), WAGOOS and AATSE (2006 [12])). Some studies have been conducted to characterise businesses serving the ocean observing community and beyond, providing ocean measurement, observation and forecasting systems, but also the intermediaries using marine data to develop value-added products and services (Rayner, Gouldman and Willis, 2018 [13]; ERISS Corporation, 2016 [14]).…”

Section: Novelty Of the Analysismentioning

confidence: 99%

Value chains in public marine data

Jolly

Jolliffe

Postlethwaite

et al. 2021

OECD Science, Technology and Industry Working Papers

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Marine data play a crucial role for many scientific disciplines, as well as for very diverse operational services such as fisheries management, environmental planning, marine conservation, weather forecasting, or port management. The information derived from marine data is also increasingly finding its way into a wide and varied range of public policy arenas and private industries. Collecting, distributing and archiving public marine data provide benefits to society at large, however as with all public investments, assessments are needed to provide evidence to decision makers. Based on an original survey of UK marine data users, this paper explores pathways through which marine data are used and transformed into actionable information, creating systematised value chains for the first time. The analysis unveils trends in current marine data uses in the UK and key benefits of data uses. The paper lays the foundations for further OECD work with the marine data community.

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“…There are many ship route design methods based on heuristic algorithm, such as Dijkstra algorithm, genetic algorithm, ant colony algorithm, A* algorithm. In order to avoid problems such as local optimal solution and long calculation time, many researchers have proposed improved methods combining other relevant algorithms (Lee et al 2018, Vettor and Guedes Soares 2016, Roh 2013.…”

Section: Ship Route Planningmentioning

confidence: 99%

Ship Route Planning Using Historical Trajectories Derived from AIS Data

He¹,

Zhang²,

Zhang³

et al. 2019

TransNav

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Ship route planning is one of the key issues in enhancing traffic safety and efficiency. Many route planning methods have been developed, but most of them are based on the information from charts. This paper proposes a method to generate shipping routes based on historical ship tracks. The ship's historical route information was obtained by processing the AIS data. From which the ship turning point was extracted and clustered as nodes. The ant colony algorithm was used to generate the optimize route. The ship AIS data of the Three Gorges dam area was selected as a case study. The ships' optimized route was generated, and further compared with the actual ship's navigation trajectory. The results indicate that there is space of improvement for some of the trajectories, especially near the turning areas.

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Determination of an economical shipping route considering the effects of sea state for lower fuel consumption

Cited by 46 publications

References 2 publications

ISO 15016:2015-Based Method for Estimating the Fuel Oil Consumption of a Ship

ISO 15016:2015-Based Method for Estimating the Fuel Oil Consumption of a Ship

Value chains in public marine data

Ship Route Planning Using Historical Trajectories Derived from AIS Data

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