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Ship routing optimization using bacterial foraging optimization algorithm for safety and efficient navigation

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 13 No. 2 (2023)

DOI
10.11591/ijece.v13i2.pp2309-2315
ISSN
2722-2578, 2088-8708
Published
2023-04-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Efficient operation plays a vital role to develop a sustainable shipping fleet with cost competitive. The requirements for economic efficiency, energy efficiency, reducing emissions, and increasing safety and security lead to an innovative model in the optimal weather routing system. The vessel routing is influenced by the quality of meteorological and oceanographic data such as wind, waves, and currents. In this study, the model optimization of weather routing considers the meteorological and oceanographic information, ship's characteristics combined with an adaptive bacterial foraging optimization algorithm (BFOA) will be introduced and applied to the ship’ navigation at sea. The simulation results will be evaluated the effectiveness and reliability of the model. This model will support ships’ navigation to be safer and more comfortable, operate more efficiently and reduce emissions.

Collaboration network of the authors

4 authors · 6 co-authorship links · 3 across different organisations

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  • Vietnam Maritime University
  • Mokpo National Maritime University
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
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