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2022 Journal Impact Factor - 0.6
2022 CiteScore - 1.7
ISSN 2083-6473
ISSN 2083-6481 (electronic version)
Editor-in-Chief
Associate Editor
Prof. Tomasz Neumann
Published by
TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
e-mail transnav@umg.edu.pl
Optimization of Daily Operations in the Marine Industry Using Ant Colony Optimization (ACO)-An Artificial Intelligence (AI) Approach
1 University of Tasmania, Launceston, Australia
2 Memorial University of Newfoundland, Newfoundland and Labrador, St. John’s, Canada
2 Memorial University of Newfoundland, Newfoundland and Labrador, St. John’s, Canada
ABSTRACT: The maritime industry plays a crucial role in the global economy, with roughly 90% of world trade being conducted through the use of merchant ships and more than a million seafarers. Despite recent efforts to improve reliability and ship structure, the heavy dependence on human performance has led to a high number of casualties in the industry. Decision errors are the primary cause of maritime accidents, with factors such as lack of situational awareness and attention deficit contributing to these errors. To address this issue, the study proposes an Ant Colony Optimization (ACO) based algorithm to design and validate a verified set of instructions for performing each daily operational task in a standardised manner. This AI-based approach can optimise the path for complex tasks, provide clear and sequential instructions, improve efficiency, and reduce the likelihood of human error by minimising personal preference and false assumptions. The proposed solution can be transformed into a globally accessible, standardised instructions manual, which can significantly contribute to minimising human error during daily operational tasks on ships.
KEYWORDS: Maritime Transport, Formal Safety Assessment (FSA), International Maritime Organization (IMO), Safety of Life at Sea (SOLAS) Convention, International Safety Management (ISM) Code, Ant Colony Optimization (ACO), Artificial Intelligence (AI), Algorithms
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Citation note:
Sardar A., Anantharaman M., Garaniya V., Khan F.: Optimization of Daily Operations in the Marine Industry Using Ant Colony Optimization (ACO)-An Artificial Intelligence (AI) Approach. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 17, No. 2, doi:10.12716/1001.17.02.04, pp. 289-295, 2023
Authors in other databases:
Abdullah Sardar:
Mohan Anantharaman:
orcid.org/0000-0001-9574-7753
55757583200
orcid.org/0000-0001-9574-7753
55757583200
LqAXS6gAAAAJOther publications of authors:
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