Development of voyage optimization algorithms for sustainable shipping and their impact to ship design
Doktorsavhandling, 2020

The environmental impacts from shipping and the societal challenges of human and property losses caused by ship accidents are pressuring the shipping industry to improve its energy efficiency and enhance ship safety. Voyage optimization is such an effective measure that has been widely adopted in today’s shipping market. The voyage optimization algorithm is the dominant part of any voyage optimization methods. The main objective of this thesis is to develop sophisticated voyage optimization algorithms, explore their applications to sustainable ship operations, and study its impact on ship fatigue design.

In this thesis, five commonly used voyage optimization algorithms are first implemented and compared to provide a foundation for understanding optimization algorithms. A three-dimensional Dijkstra’s algorithm is then developed with further improvement based on the comparison. It can provide globally optimal solutions and conducting multi-objective voyage optimization. An engine-power based multi-objective optimization algorithm is proposed for the aid of ship operations with power-setting in their navigation system. Furthermore, the influence of the uncertainties from voyage optimization inputs, e.g., metocean forecast, implemented ship performance models and voyage optimization algorithms, on the optimization results is investigated. Moreover, the capabilities of the proposed voyage optimization algorithms to handle other optimization objectives, i.e., less fatigue damage accumulation and lower fatigue crack propagation rate, is also investigated. Meanwhile, two statistical wave models are compared to study the variation of a ship’s encountered wave environment for ship fatigue design. The impact of voyage optimization aided operations on a ship’s encountered wave environments and fatigue life assessment is also researched in this thesis.

The three-dimensional Dijkstra’s algorithm addresses the limitations of conventional voyage optimization algorithms and allows for voluntary speed variation. It has a great potential of saving fuel up to about 12% in comparison with the case study ship’s actual sailing routes. The ship engine setting-based optimization algorithm provides a scheme based on a genetic algorithm and dynamic programming concept. It has the potential to save fuel up to approximately 14.5% compared to the actual sailing routes. This study also shows that metocean uncertainties in the voyage optimization process have great influence on the optimization results, i.e., 3-10% difference in fuel consumption for the same voyage optimization method. In addition, statistical wave models have been proven to capture ship-encountered wave statistics. It is also shown that the actual wave environments encountered by ships differ significantly from the wave scatter diagram provided by class guidelines. A good voyage optimization method can help to extend a ship’s fatigue life by at least 50%.

Keywords: Dijkstra’s algorithm; Energy efficiency; Expected time of arrival (ETA); Genetic algorithm; Metocean forecast; Ship safety; Sustainable shipping; Voyage optimization algorithms.

Voyage optimization algorithms.

Energy efficiency

Sustainable shipping

Ship safety

Metocean forecast

Dijkstra’s algorithm

Genetic algorithm

Expected time of arrival (ETA)

Remote defense via zoom
Opponent: Professor Atilla Incecik, University of Strathclyde, UK

Författare

Helong Wang

Chalmers, Mekanik och maritima vetenskaper, Marin teknik

Voyage optimization for mitigating ship structural failure due to crack propagation

Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability,; Vol. 233(2019)p. 5-17

Artikel i vetenskaplig tidskrift

A Three-Dimensional Dijkstra’s algorithm for multi-objective ship voyage optimization

Ocean Engineering,; Vol. 186(2019)

Artikel i vetenskaplig tidskrift

Comparison of two statistical wave models for fatigue and fracture analysis of ship structures

Ocean Engineering,; Vol. Vol.187(2019)

Artikel i vetenskaplig tidskrift

Wang, H., Lang, X., and Mao, W. (2019). A ship engine power-based voyage optimization method by combing genetic algorithm and dynamic programming concepts.

Lang, X., Wang, H., Mao, W., and Osawa, N. (2020). Impact of voyage optimizations aided operation on a ship’s fatigue design.

Benchmark study of five optimization algorithms for weather routing

International Conference on Offshore Mechanics and Arctic Engineering,; Vol. OMAE2017-61022(2017)

Paper i proceeding

Shipping is recognized as the most efficient and cost-effective transportation mode and carries approximately 90% of world trade. It provides a dependable, low-cost means of transporting goods globally. However, the environmental impacts from shipping and the societal challenges of human and property losses caused by ship accidents are pressuring the shipping industry to improve its energy efficiency and enhance ship safety. Voyage optimization is such an effective measure that has been widely adopted in today’s shipping market. The voyage optimization algorithm is the dominant part of any voyage optimization methods.

This thesis contributes by developing sophisticated voyage optimization algorithms, exploring their applications to sustainable ship operations, and studying its impact on ship fatigue design. the developed voyage optimization algorithms provide optimal routes that can help the ships save fuel and reduce the effect of weather damage to the ship. Moreover, in this thesis, it is also found that voyage optimization can help to mitigate ship structure failure due to fatigue crack propagation and fatigue damage accumulation. Finally, our research can lead the ship sailing in a more energy-efficient and safe way.

EONav - Earth Observation for Maritime Navigation

Europeiska kommissionen (Horisont 2020), 2016-05-01 -- 2019-04-30.

EcoSail - Miljövänlig och kunddriven Sailplan optimeringstjänst

Europeiska kommissionen (Horisont 2020), 2018-11-01 -- 2021-04-30.

Drivkrafter

Hållbar utveckling

Styrkeområden

Transport

Energi

Ämneskategorier

Beräkningsmatematik

Marin teknik

Datavetenskap (datalogi)

ISBN

978-91-7905-259-1

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4726

Utgivare

Chalmers tekniska högskola

Remote defense via zoom

Online

Opponent: Professor Atilla Incecik, University of Strathclyde, UK

Mer information

Senast uppdaterat

2020-04-02