An enhanced adaptive butterfly optimization algorithm rigorously verified on engineering problems and implemented to ISAR image motion compensation

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dc.authoridUSTUN, Deniz/0000-0002-5229-4018
dc.contributor.authorUstun, Deniz
dc.date.accessioned2025-03-17T12:25:42Z
dc.date.available2025-03-17T12:25:42Z
dc.date.issued2020
dc.departmentTarsus Üniversitesi
dc.description.abstractPurpose This study aims to evolve an enhanced butterfly optimization algorithm (BOA) with respect to convergence and accuracy performance for numerous benchmark functions, rigorous constrained engineering design problems and an inverse synthetic aperture radar (ISAR) image motion compensation. Design/methodology/approach Adaptive BOA (ABOA) is thus developed by incorporating spatial dispersal strategy to the global search and inserting the fittest solution to the local search, and hence its exploration and exploitation abilities are improved. Findings The accuracy and convergence performance of ABOA are well verified via exhaustive comparisons with BOA and its existing variants such as improved BOA (IBOA), modified BOA (MBOA) and BOA with Levy flight (BOAL) in terms of various precise metrics through 15 classical and 12 conference on evolutionary computation (CEC)-2017 benchmark functions. ABOA has outstanding accuracy and stability performance better than BOA, IBOA, MBOA and BOAL for most of the benchmarks. The design optimization performance of ABOA is also evaluated for three constrained engineering problems such as welded beam design, spring design and gear train design and the results are compared with those of BOA, MBOA and BOA with chaos. ABOA, therefore, optimizes engineering designs with the most optimal variables. Furthermore, a validation is performed through translational motion compensation (TMC) of the ISAR image for an aircraft, which includes blurriness. In TMC, the motion parameters such as velocity and acceleration of target are optimally predicted by the optimization algorithms. The TMC results are elaborately compared with BOA, IBOA, MBOA and BOAL between each other in view of images, motion parameter and numerical image measuring metrics. Originality/value The outperforming results reflect the optimization and design successes of ABOA which is enhanced by establishing better global and local search abilities over BOA and its existing variants.
dc.identifier.doi10.1108/EC-02-2020-0126
dc.identifier.endpage3566
dc.identifier.issn0264-4401
dc.identifier.issn1758-7077
dc.identifier.issue9
dc.identifier.scopus2-s2.0-85086592373
dc.identifier.scopusqualityQ2
dc.identifier.startpage3543
dc.identifier.urihttps://doi.org/10.1108/EC-02-2020-0126
dc.identifier.urihttps://hdl.handle.net/20.500.13099/1812
dc.identifier.volume37
dc.identifier.wosWOS:000541871400001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorUstun, Deniz
dc.language.isoen
dc.publisherEmerald Group Publishing Ltd
dc.relation.ispartofEngineering Computations
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250316
dc.subjectEngineering design
dc.subjectButterfly optimization algorithm
dc.subjectISAR imaging
dc.subjectEnhanced algorithm
dc.subjectBenchmark functions
dc.subjectCEC functions
dc.subjectMotion compensation
dc.titleAn enhanced adaptive butterfly optimization algorithm rigorously verified on engineering problems and implemented to ISAR image motion compensation
dc.typeArticle

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