Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/108810
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dc.contributorDepartment of Electrical and Electronic Engineering-
dc.creatorQais, MH-
dc.creatorHasanien, HM-
dc.creatorAlghuwainem, S-
dc.creatorLoo, KH-
dc.date.accessioned2024-08-27T04:40:43Z-
dc.date.available2024-08-27T04:40:43Z-
dc.identifier.urihttp://hdl.handle.net/10397/108810-
dc.language.isoenen_US
dc.publisherMDPI AGen_US
dc.rights© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Qais MH, Hasanien HM, Alghuwainem S, Loo KH. Propagation Search Algorithm: A Physics-Based Optimizer for Engineering Applications. Mathematics. 2023; 11(20):4224 is available at https://doi.org/10.3390/math11204224.en_US
dc.subjectAlgorithmsen_US
dc.subjectEngineering optimizationen_US
dc.subjectMetaheuristicsen_US
dc.subjectPropagation search algorithmen_US
dc.titlePropagation search algorithm : a physics-based optimizer for engineering applicationsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume11-
dc.identifier.issue20-
dc.identifier.doi10.3390/math11204224-
dcterms.abstractFor process control in engineering applications, the fewer the coding lines of optimization algorithms, the more applications there are. Therefore, this work develops a new straightforward metaheuristic optimization algorithm named the propagation search algorithm (PSA), stirred by the wave propagation of the voltage and current along long transmission lines. The mathematical models of the voltage and current are utilized in modeling the PSA, where the voltage and current are the search agents. The propagation constant of the transmission line is the control parameter for the exploitation and exploration of the PSA. After that, the robustness of the PSA is verified using 23 famous testing functions. The statistical tests, comprising mean, standard deviation, and p-values, for 20 independent optimization experiments are utilized to confirm the robustness of the PSA to find the best result and the significant difference between the outcomes of the PSA and those of the compared algorithms. Finally, the proposed PSA is applied to find the optimum design parameters of four engineering design problems, including a three-bar truss, compression spring, pressure vessel, and welded beam. The outcomes show that the PSA converges to the best solutions very quickly, which can be applied to those applications that require a fast response.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationMathematics, Oct. 20223, v. 11, no. 20, 4224-
dcterms.isPartOfMathematics-
dcterms.issued2023-10-
dc.identifier.scopus2-s2.0-85175529984-
dc.identifier.eissn2227-7390-
dc.identifier.artn4224-
dc.description.validate202408 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextDeputyship for Research and Innovation, “Ministry of Education” in Saudi Arabiaen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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