Advances in Manta Ray Foraging Optimization: A Comprehensive Survey

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dc.authoridBahman Arasteh / 0000-0001-5202-6315
dc.authoridSoleimanian Gharehchopogh, Farhad/0000-0003-1588-1659
dc.authorwosidBahman Arasteh / AAN-9555-2021
dc.contributor.authorGharehchopogh, Farhad Soleimanian
dc.contributor.authorGhafouri, Shafi
dc.contributor.authorNamazi, Mohammad
dc.contributor.authorArasteh, Bahman
dc.date.accessioned2024-05-19T14:45:45Z
dc.date.available2024-05-19T14:45:45Z
dc.date.issued2024
dc.departmentİstinye Üniversitesien_US
dc.description.abstractThis paper comprehensively analyzes the Manta Ray Foraging Optimization (MRFO) algorithm and its integration into diverse academic fields. Introduced in 2020, the MRFO stands as a novel metaheuristic algorithm, drawing inspiration from manta rays' unique foraging behaviors-specifically cyclone, chain, and somersault foraging. These biologically inspired strategies allow for effective solutions to intricate physical challenges. With its potent exploitation and exploration capabilities, MRFO has emerged as a promising solution for complex optimization problems. Its utility and benefits have found traction in numerous academic sectors. Since its inception in 2020, a plethora of MRFO-based research has been featured in esteemed international journals such as IEEE, Wiley, Elsevier, Springer, MDPI, Hindawi, and Taylor & Francis, as well as at international conference proceedings. This paper consolidates the available literature on MRFO applications, covering various adaptations like hybridized, improved, and other MRFO variants, alongside optimization challenges. Research trends indicate that 12%, 31%, 8%, and 49% of MRFO studies are distributed across these four categories respectively.en_US
dc.identifier.doi10.1007/s42235-024-00481-y
dc.identifier.endpage990en_US
dc.identifier.issn1672-6529
dc.identifier.issn2543-2141
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85186179054en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage953en_US
dc.identifier.urihttps://doi.org10.1007/s42235-024-00481-y
dc.identifier.urihttps://hdl.handle.net/20.500.12713/5332
dc.identifier.volume21en_US
dc.identifier.wosWOS:001172839100008en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Singapore Pte Ltden_US
dc.relation.ispartofJournal of Bionic Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectManta Ray Foraging Optimizationen_US
dc.subjectMetaheuristic Algorithmsen_US
dc.subjectHybridizationen_US
dc.subjectImproveden_US
dc.subjectOptimizationen_US
dc.titleAdvances in Manta Ray Foraging Optimization: A Comprehensive Surveyen_US
dc.typeReview Articleen_US

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