Vol.15, No.3, August 2026.                                                                                                                                                                          ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333

TEM Journal

TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS

Association for Information Communication Technology Education and Science

Nature-Inspired Metaheuristics for Solving Complex Optimization Problems in the Maritime Industry

Matej Šuper, Marko Gulić, Lovro Maglić, Ana Perić Hadžić

© 2026 Matej Šuper, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)

Citation Information: TEM Journal. Volume 15, Issue 3, Pages 2321-2339, ISSN 2217-8309, DOI: 10.18421/TEM153-24, August 2026.

Received: 28 August 2025.
Revised: 10 January 2026.
Accepted: 17 January 2026.
Published: 27 August 2026.

Abstract:

The maritime industry is crucial for global trade and the promotion of economic development. However, it faces major challenges, especially in tackling complex NP-hard problems that require effective decision support. To overcome these challenges, nature-inspired metaheuristic algorithms have proven to be powerful tools for optimization processes in the maritime sector. This paper provides a systematic overview of the application of these algorithms to various maritime problems, including collision avoidance, ship routing, tugboat scheduling, evacuation planning, container stowage, berth allocation, quay crane allocation, transport optimisation, search and rescue operations, hydrant location optimization and the damage stability problem. In addition, new optimisation algorithms are constantly being presented in the literature to further improve performance in various applications. As shown in this paper, recent algorithms such as The Pelican Optimization Algorithm, The Squirrel Search Optimization Algorithm, The Snow Leopard Optimization Algorithm and The Deer Hunting Optimization Algorithm have outperformed traditional metaheuristics in optimising known test functions, suggesting that they may offer promising improvements for solving complex maritime optimization problems.

Keywords – Algorithm comparison, maritime industry, nature-inspired metaheuristics, optimization.

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