Marine predators algorithm: A comprehensive review
Marine predators algorithm (MPA) is a recently proposed metaheuristic algorithm that mimics the marine predators behavior when attacking their preys. Recently, the MPA has been broadly employed to tackle numerous optimization problems in various research areas and has confirmed its supremacy over a...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-06-01
|
| Series: | Machine Learning with Applications |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666827023000245 |
| _version_ | 1827917635341254656 |
|---|---|
| author | Sylvère Mugemanyi Zhaoyang Qu François Xavier Rugema Yunchang Dong Lei Wang Christophe Bananeza Arcade Nshimiyimana Emmanuel Mutabazi |
| author_facet | Sylvère Mugemanyi Zhaoyang Qu François Xavier Rugema Yunchang Dong Lei Wang Christophe Bananeza Arcade Nshimiyimana Emmanuel Mutabazi |
| author_sort | Sylvère Mugemanyi |
| collection | DOAJ |
| description | Marine predators algorithm (MPA) is a recently proposed metaheuristic algorithm that mimics the marine predators behavior when attacking their preys. Recently, the MPA has been broadly employed to tackle numerous optimization problems in various research areas and has confirmed its supremacy over a large number of the metaheuristic algorithms regard to convergence speed and accuracy thanks to its simplicity, flexible implementation and few adjustable parameters requirements. A comprehensive review of the MPA is presented in this paper along with its variants such as binary, discrete, modifications, hybridizations, chaotic, quantum and multi-objective versions. This paper also reviews various applications of MPA in electrical engineering, computer science, medicine, etc. Moreover, further research directions for MPA are suggested. The source code of the MPA can be found at: http://www.alimirjalili.com/MPA.html. |
| first_indexed | 2024-03-13T03:31:13Z |
| format | Article |
| id | doaj.art-47c66fbb7c284ba5be1931f9ce64751f |
| institution | Directory Open Access Journal |
| issn | 2666-8270 |
| language | English |
| last_indexed | 2024-03-13T03:31:13Z |
| publishDate | 2023-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Machine Learning with Applications |
| spelling | doaj.art-47c66fbb7c284ba5be1931f9ce64751f2023-06-24T05:19:42ZengElsevierMachine Learning with Applications2666-82702023-06-0112100471Marine predators algorithm: A comprehensive reviewSylvère Mugemanyi0Zhaoyang Qu1François Xavier Rugema2Yunchang Dong3Lei Wang4Christophe Bananeza5Arcade Nshimiyimana6Emmanuel Mutabazi7Department of Electronics and Telecommunication Technology, Integrated Polytechnic Regional College Tumba, P.O. Box 6638 Rulindo, Rwanda; Corresponding author.School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China; Jilin Engineering Technology Research Center of Intelligent Electric Power Big Data Processing, Jilin 132012, ChinaDepartment of Business Information Technology, College of Business and Economics, University of Rwanda, P.O. Box 4285 Kigali, RwandaSchool of Electrical Engineering, Northeast Electric Power University, Jilin 132012, ChinaSchool of Electrical Engineering, Northeast Electric Power University, Jilin 132012, ChinaSchool of Energy and Electrical Engineering, Hohai University, Nanjing 210098, ChinaDepartment of Electronics and Telecommunication Technology, Integrated Polytechnic Regional College Tumba, P.O. Box 6638 Rulindo, RwandaCollege of IoT Engineering, Hohai University, Changzhou 310000, ChinaMarine predators algorithm (MPA) is a recently proposed metaheuristic algorithm that mimics the marine predators behavior when attacking their preys. Recently, the MPA has been broadly employed to tackle numerous optimization problems in various research areas and has confirmed its supremacy over a large number of the metaheuristic algorithms regard to convergence speed and accuracy thanks to its simplicity, flexible implementation and few adjustable parameters requirements. A comprehensive review of the MPA is presented in this paper along with its variants such as binary, discrete, modifications, hybridizations, chaotic, quantum and multi-objective versions. This paper also reviews various applications of MPA in electrical engineering, computer science, medicine, etc. Moreover, further research directions for MPA are suggested. The source code of the MPA can be found at: http://www.alimirjalili.com/MPA.html.http://www.sciencedirect.com/science/article/pii/S2666827023000245Marine predator algorithmMetaheuristic algorithmSwarm intelligenceNature-inspired algorithmOptimizationVariant |
| spellingShingle | Sylvère Mugemanyi Zhaoyang Qu François Xavier Rugema Yunchang Dong Lei Wang Christophe Bananeza Arcade Nshimiyimana Emmanuel Mutabazi Marine predators algorithm: A comprehensive review Machine Learning with Applications Marine predator algorithm Metaheuristic algorithm Swarm intelligence Nature-inspired algorithm Optimization Variant |
| title | Marine predators algorithm: A comprehensive review |
| title_full | Marine predators algorithm: A comprehensive review |
| title_fullStr | Marine predators algorithm: A comprehensive review |
| title_full_unstemmed | Marine predators algorithm: A comprehensive review |
| title_short | Marine predators algorithm: A comprehensive review |
| title_sort | marine predators algorithm a comprehensive review |
| topic | Marine predator algorithm Metaheuristic algorithm Swarm intelligence Nature-inspired algorithm Optimization Variant |
| url | http://www.sciencedirect.com/science/article/pii/S2666827023000245 |
| work_keys_str_mv | AT sylveremugemanyi marinepredatorsalgorithmacomprehensivereview AT zhaoyangqu marinepredatorsalgorithmacomprehensivereview AT francoisxavierrugema marinepredatorsalgorithmacomprehensivereview AT yunchangdong marinepredatorsalgorithmacomprehensivereview AT leiwang marinepredatorsalgorithmacomprehensivereview AT christophebananeza marinepredatorsalgorithmacomprehensivereview AT arcadenshimiyimana marinepredatorsalgorithmacomprehensivereview AT emmanuelmutabazi marinepredatorsalgorithmacomprehensivereview |