The simulation of east-bound transoceanic voyages according to ocean-current sailing based on Particle Swarm Optimization in the weather routing system

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)

Abstract

In this study, a Particle Swarm Optimizing (PSO) method would be applied to the dynamic routing algorithm of our original three-dimensional modified isochrone (3DMI) method for improving efficiencies of time and fuel consumption by ocean-current routes in the North Pacific Ocean. By comparing the east-bound voyages based on the Ocean-Current (OC) sailing with the ones based on the Great-Circle (GC) sailing in case of dynamic environments, performances of ocean-going ships would be presented including the safety factor, i.e. significant roll response. The ship weather routing system is essentially constructed by four modules, consisting of ship-motion module, ocean-environmental module, navigation module and routing-optimization module. After establishing the database of 6-DOF motion response for different combinations of ship courses and sailing speeds from the ship-motion module, ship performances can be estimated according to the encountered sea state interpolated by weather forecasting data from the ocean-environmental module. For different purposes of navigation, the reference routes can be subsequently determined by the Navigation module according to the selection of GC or OC sailing. Eventually, the optimal routes are obtained by setting objectives and constraints in the objective function of the routing-optimization module.

Original languageEnglish
Pages (from-to)219-236
Number of pages18
JournalMarine Structures
Volume59
DOIs
Publication statusPublished - 2018 May

All Science Journal Classification (ASJC) codes

  • General Materials Science
  • Ocean Engineering
  • Mechanics of Materials
  • Mechanical Engineering

Fingerprint

Dive into the research topics of 'The simulation of east-bound transoceanic voyages according to ocean-current sailing based on Particle Swarm Optimization in the weather routing system'. Together they form a unique fingerprint.

Cite this