MetOcean Data Drived Voyage Optimization Using Genetic Algorithm
Paper i 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

Författare

Helong Wang

Chalmers, Mekanik och maritima vetenskaper, Marin teknik

Wengang Mao

Chalmers, Mekanik och maritima vetenskaper, Marin teknik

Leif Eriksson

Chalmers, Rymd-, geo- och miljövetenskap, Mikrovågs- och optisk fjärranalys

Proceedings of the International Offshore and Polar Engineering Conference

10986189 (ISSN) 15551792 (eISSN)

697-705

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

EONav - Earth Observation for Maritime Navigation

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

Utforska innovativa lösningar för arktisk sjöfart

STINT, 2017-05-01 -- 2020-06-30.

Drivkrafter

Hållbar utveckling

Innovation och entreprenörskap

Styrkeområden

Transport

Energi

Ämneskategorier

Teknisk mekanik

Transportteknik och logistik

Fundament

Grundläggande vetenskaper

Mer information

Senast uppdaterat

2019-01-16