MetOcean Data Drived Voyage Optimization Using Genetic Algorithm
Paper in proceeding, 2018

Conventional voyage optimization algorithms often follow similar estimation procedures to design a ship’s optimal sailing courses and schedules, through first generate waypoints/grids along a ship’s sailing area, construct candidate routes, and implement a searching method to find the optimal route with respect to specific objectives. One important variable to control a ship’s operation is the navigation condition, which may lead to the fact that the planned optimum route is only a locally optimal solution for a ship’s route planning. In this paper, a hybrid optimization algorithm is proposed to provide globally optimum route planning using Dijkstra’s algorithm and genetic algorithm.

Voyage optimization algorithm

ETA

genetic algorithm

3D Graph

Dijkstra’s algorithm

fuel consumption

Author

Helong Wang

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

Wengang Mao

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

Leif Eriksson

Chalmers, Space, Earth and Environment, Microwave and Optical Remote Sensing

Proceedings of the International Offshore and Polar Engineering Conference

10986189 (ISSN) 15551792 (eISSN)

Vol. 2018-June 697-705
9781880653876 (ISBN)

28th International Ocean and Polar Engineering Conferen
Sapporo, Japan,

EONav - Earth Observation for Maritime Navigation

European Commission (EC) (EC/H2020/687537), 2016-05-01 -- 2019-04-30.

Explore innovative solutions for arctic shipping

The Swedish Foundation for International Cooperation in Research and Higher Education (STINT) (Dnr:CH2016-6673), 2017-05-01 -- 2020-06-30.

Driving Forces

Sustainable development

Innovation and entrepreneurship

Areas of Advance

Transport

Energy

Subject Categories

Applied Mechanics

Transport Systems and Logistics

Roots

Basic sciences

More information

Latest update

4/5/2022 6