Voyage optimization combining genetic algorithm and dynamic programming for fuel/emissions reduction
Artikel i vetenskaplig tidskrift, 2021

Deterministic optimization algorithms generate optimal routes/paths and speeds along ship voyages. However, a ship can rarely follow pre-defined speeds because dynamic sea environments lead to continuous speed variation. In this paper, a voyage optimization method is proposed to optimize ship engine power to reduce fuel and air emissions. It is a combination of dynamic programming and genetic algorithm to solve voyage planning in three-dimensions. In this method, the engine power is discretized into several levels. The potential benefit of using this algorithm is investigated by a medium-size chemical tanker. A ship's actual sailing is used to demonstrate benefits of the proposed method. On average 3.4% of fuel-saving and emission reduction can be achieved than state-of-the-art deterministic methods. If compared with the actual full-scale measurements, on average 5.6% reduction of fuel consumption and GHG emissions (about 275 tons) can be expected by the proposed method for the six case study voyages.

Voyage optimization

Dynamic programming


Genetic algorithm

Expected Time of Arrival (ETA)

Emission reduction


Helong Wang

Chalmers, Mekanik och maritima vetenskaper, Marin teknik

Xiao Lang

Chalmers, Mekanik och maritima vetenskaper, Marin teknik

Wengang Mao

Chalmers, Mekanik och maritima vetenskaper, Marin teknik

Transportation Research Part D: Transport and Environment

1361-9209 (ISSN)

Vol. 90 102670


Hållbar utveckling






Marin teknik



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