Review on ship speed optimization

YUAN Yu-peng; WANG Kang-yu; YIN Qi-zhi; YAN Xin-ping

doi:10.19818/j.cnki.1671-1637.2020.06.002

Volume 20 Issue 6

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Article Navigation > Journal of Traffic and Transportation Engineering > 2020 > 20(6): 18-34

YUAN Yu-peng, WANG Kang-yu, YIN Qi-zhi, YAN Xin-ping. Review on ship speed optimization[J]. Journal of Traffic and Transportation Engineering, 2020, 20(6): 18-34. doi: 10.19818/j.cnki.1671-1637.2020.06.002

Citation:

YUAN Yu-peng, WANG Kang-yu, YIN Qi-zhi, YAN Xin-ping. Review on ship speed optimization[J]. Journal of Traffic and Transportation Engineering, 2020, 20(6): 18-34. doi: 10.19818/j.cnki.1671-1637.2020.06.002

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Review on ship speed optimization

doi: 10.19818/j.cnki.1671-1637.2020.06.002

School of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, Hubei, China

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National Natural Science Foundation of China 51809202

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Author Bio:
YUAN Yu-peng (1980-), male, associate professor, PhD, ypyuan@whut.edu.cn

YAN Xin-ping (1959-), male, professor, PhD, academician of Chinese academy of engineering, xpyan@whut.edu.cn
Received Date: 2020-07-26
Publish Date: 2020-06-25

Abstract

Abstract

The status of ship speed optimization research in domestic and overseas, including ship speed optimization models, fuel consumption prediction methods, solutions of ship speed optimization models, and ship energy efficiency management systems, were summarized and analyzed. The existing problems in speed optimization research were discussed, and suggestions were made to solve these problems. Analysis result shows that, under the condition in which the shipping market continues to be depressed, economic navigation will be used more widely, and research on speed optimization will remain of great significance.In terms of speed optimization models, most speed optimization models are established with carbon emission policy, influence of uncertain factors, emission control area(ECA) policy and fleet scheduling as a single optimization objective. The main optimization objectives of speed optimization models are to minimize the cost and maximize the profit. Speed should be combined with route, trim and fleet deployment optimization, and a model of speed optimization should be established considering various uncertain factors and optimization objectives in the future.In terms of fuel consumption prediction model, prediction models are mainly divided into white box, black box, and gray box models. The white box model is better in terms of model interpretability, the black box model offers better prediction performance, and the gray box model compensates for the disadvantages of the white box model and the black box model and will become the focus of future research.Data learning should be based on accurate ship data and advanced artificial intelligence algorithms to improve the prediction accuracy of fuel consumption prediction model.In terms of optimization algorithm, due to the complexity of speed optimization model, heuristic algorithm is mostly used for optimization solution. This algorithm can reduce the optimization solution time and improve the solution quality. More accurate and efficient solution algorithms need to be explored in the future.In terms of optimization strategy, the use of big data analysis can identify the influence of weather on navigation, and the use of dynamic optimization strategies can compensate for disturbances caused by environmental factors, enabling further improvement in the energy efficiency of ships.In terms of ship energy efficiency management system, the ship energy efficiency management system mainly includes navigation data acquisition, data transmission, data storage, data analysis and intelligent decision making, it has not been applied on a large scale on ships as its high cost.
- ship engineering,
- speed optimization,
- fuel consumption prediction,
- optimization algorithm,
- energy efficiency management,
- review

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References(72)

References

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