Voyage optimization combining genetic algorithm and dynamic programming for fuel/emissions reduction - Wang, Helong; Lang, Xiao; Mao, Wengang (Transportation research. Part D, Transport and environment, 2021)
•A voyage optimization method is proposed to take engine powers ship voyage planning.•The proposed method combines a genetic algorithm with dynamic programming concepts.•The proposed method is capable of multi-objective global optimization to reduce fuel and air emissions.•About 5% fuel-saving and air emissions is achieved by the method than the measured fuel cost.•About 275 tons of GHG emission can be reduced by the proposed method for the six voyages. 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.