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Marine Predator Algorithm and Related Variants: A Systematic Review

—The Marine Predators Algorithm (MPA) is classified under swarm intelligence methods based on its type of inspiration. It is a population-based metaheuristic optimization algorithm inspired by the general foraging behavior exhibited in the form of Levy and Brownian motion in ocean predators support...

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Main Authors:	Emmanuel, Philibus, Azlan, Mohd Zain, Didik Dwi, Prasetya, Mahadi, Bahari, Norfadzlan, Yusup, Rozita, Abdul Jalil, Mazlina, Abdul Majid, Azurah, A Samah
Format:	Article
Language:	English
Published:	SCIENCE & INFORMATION SAI ORGANIZATION LTD 2025
Subjects:	QA Mathematics QA75 Electronic computers. Computer science
Online Access:	http://ir.unimas.my/id/eprint/47488/1/Paper_54-Marine_Predator_Algorithm_and_Related_Variants.pdf http://ir.unimas.my/id/eprint/47488/ https://thesai.org/Downloads/Volume16No1/Paper_54-Marine_Predator_Algorithm_and_Related_Variants.pdf http://dx.doi.org/10.14569/IJACSA.2025.0160154
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id	my.unimas.ir-47488
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spelling	my.unimas.ir-474882025-02-05T01:53:37Z http://ir.unimas.my/id/eprint/47488/ Marine Predator Algorithm and Related Variants: A Systematic Review Emmanuel, Philibus Azlan, Mohd Zain Didik Dwi, Prasetya Mahadi, Bahari Norfadzlan, Yusup Rozita, Abdul Jalil Mazlina, Abdul Majid Azurah, A Samah QA Mathematics QA75 Electronic computers. Computer science —The Marine Predators Algorithm (MPA) is classified under swarm intelligence methods based on its type of inspiration. It is a population-based metaheuristic optimization algorithm inspired by the general foraging behavior exhibited in the form of Levy and Brownian motion in ocean predators supported by the policy of optimum success rate found in the biological relationship between prey and predators. The algorithm is easy to implement and robust in searching, yielding better solutions to many real-world problems. It is attracting huge and growing interest. This paper provides a systematic review of the research progress and applications of the MPA by analyzing more than 100 articles sourced from Scopus and Web of Science databases using the PRISMA approach. The study expounded the classical MPA’s workflow. It also unveiled a steady upward trend in the use of the algorithm. The research presented different improvements and variants of MPA including parameter-tuning, enhancement of the balance between exploration and exploitation, hybridization of MPA with other techniques to harness the strengths of each of the algorithms towards complementing thecweaknesses of the other, and more recently proposed advances. It further underscores the application of MPA in various areas such as Engineering, Computer Science, Mathematics, and Energy. Findings reveal several search strategies implemented to improve the algorithm’s performance. In conclusion, although MPA has been widely accepted, other areas remain yet to be applied, and some improvements are yet to be covered. These have been presented as recommendations for future research direction. SCIENCE & INFORMATION SAI ORGANIZATION LTD 2025-01 Article PeerReviewed text en http://ir.unimas.my/id/eprint/47488/1/Paper_54-Marine_Predator_Algorithm_and_Related_Variants.pdf Emmanuel, Philibus and Azlan, Mohd Zain and Didik Dwi, Prasetya and Mahadi, Bahari and Norfadzlan, Yusup and Rozita, Abdul Jalil and Mazlina, Abdul Majid and Azurah, A Samah (2025) Marine Predator Algorithm and Related Variants: A Systematic Review. International Journal of Advanced Computer Science and Applications (IJACSA), 16 (1). pp. 544-568. ISSN 2156-5570, 2158-107X https://thesai.org/Downloads/Volume16No1/Paper_54-Marine_Predator_Algorithm_and_Related_Variants.pdf http://dx.doi.org/10.14569/IJACSA.2025.0160154
institution	Universiti Malaysia Sarawak
building	Centre for Academic Information Services (CAIS)
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Sarawak
content_source	UNIMAS Institutional Repository
url_provider	http://ir.unimas.my/
language	English
topic	QA Mathematics QA75 Electronic computers. Computer science
spellingShingle	QA Mathematics QA75 Electronic computers. Computer science Emmanuel, Philibus Azlan, Mohd Zain Didik Dwi, Prasetya Mahadi, Bahari Norfadzlan, Yusup Rozita, Abdul Jalil Mazlina, Abdul Majid Azurah, A Samah Marine Predator Algorithm and Related Variants: A Systematic Review
description	—The Marine Predators Algorithm (MPA) is classified under swarm intelligence methods based on its type of inspiration. It is a population-based metaheuristic optimization algorithm inspired by the general foraging behavior exhibited in the form of Levy and Brownian motion in ocean predators supported by the policy of optimum success rate found in the biological relationship between prey and predators. The algorithm is easy to implement and robust in searching, yielding better solutions to many real-world problems. It is attracting huge and growing interest. This paper provides a systematic review of the research progress and applications of the MPA by analyzing more than 100 articles sourced from Scopus and Web of Science databases using the PRISMA approach. The study expounded the classical MPA’s workflow. It also unveiled a steady upward trend in the use of the algorithm. The research presented different improvements and variants of MPA including parameter-tuning, enhancement of the balance between exploration and exploitation, hybridization of MPA with other techniques to harness the strengths of each of the algorithms towards complementing thecweaknesses of the other, and more recently proposed advances. It further underscores the application of MPA in various areas such as Engineering, Computer Science, Mathematics, and Energy. Findings reveal several search strategies implemented to improve the algorithm’s performance. In conclusion, although MPA has been widely accepted, other areas remain yet to be applied, and some improvements are yet to be covered. These have been presented as recommendations for future research direction.
format	Article
author	Emmanuel, Philibus Azlan, Mohd Zain Didik Dwi, Prasetya Mahadi, Bahari Norfadzlan, Yusup Rozita, Abdul Jalil Mazlina, Abdul Majid Azurah, A Samah
author_facet	Emmanuel, Philibus Azlan, Mohd Zain Didik Dwi, Prasetya Mahadi, Bahari Norfadzlan, Yusup Rozita, Abdul Jalil Mazlina, Abdul Majid Azurah, A Samah
author_sort	Emmanuel, Philibus
title	Marine Predator Algorithm and Related Variants: A Systematic Review
title_short	Marine Predator Algorithm and Related Variants: A Systematic Review
title_full	Marine Predator Algorithm and Related Variants: A Systematic Review
title_fullStr	Marine Predator Algorithm and Related Variants: A Systematic Review
title_full_unstemmed	Marine Predator Algorithm and Related Variants: A Systematic Review
title_sort	marine predator algorithm and related variants: a systematic review
publisher	SCIENCE & INFORMATION SAI ORGANIZATION LTD
publishDate	2025
url	http://ir.unimas.my/id/eprint/47488/1/Paper_54-Marine_Predator_Algorithm_and_Related_Variants.pdf http://ir.unimas.my/id/eprint/47488/ https://thesai.org/Downloads/Volume16No1/Paper_54-Marine_Predator_Algorithm_and_Related_Variants.pdf http://dx.doi.org/10.14569/IJACSA.2025.0160154
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score	13.244413

Marine Predator Algorithm and Related Variants: A Systematic Review

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