Fitness Distance Balance Based LSHADE Algorithm for Energy Hub Economic Dispatch Problem

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dc.authoridguvenc, ugur/0000-0002-5193-7990
dc.authorwosidguvenc, ugur/H-3029-2011
dc.contributor.authorÖzkaya, Burçin
dc.contributor.authorGüvenç, Uğur
dc.contributor.authorBingöl, Okan
dc.date.accessioned2023-07-26T11:55:01Z
dc.date.available2023-07-26T11:55:01Z
dc.date.issued2022
dc.departmentDÜ, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.description.abstractThis paper presents an improved version of Linear Population Size Reduction Success History Based Adaptive Differential Evolution (LSHADE) algorithm for solving global optimization problems. Fitness Distance Balance (FDB) selection method was used to redesign the mutation operator in order to enhance the search performance of the LSHADE algorithm. In order to test and validate the performance of the proposed algorithm, a comprehensive experimental study was carried out. For this purpose, it was tested on the CEC14 and CEC17 benchmark problems, consisting of different problem types and dimensions. Results of the FDB-LSHADE was compared to the performance of 8 other up-to-date and highly preferred metaheuristic search (MHS) algorithms. According to Friedman test results, the proposed FDBLSHADE algorithm ranked first among the all competing algorithms. Moreover, the proposed algorithm was used to solve single- and multi-objective energy hub economic dispatch (EHED) problems, which were a non-convex, a nonlinear, and high dimensional problems. To analyze the results of the proposed algorithm obtained from experimental studies, two non-parametric statistical methods, which are Wilcoxon and Friedman tests, were used. The simulation results of the proposed algorithm were compared to the results of the 8 other MHS algorithms. The results demonstrated that the FDB-LSHADE was a superior performance compared to other MHS algorithms for solving both benchmark and EHED problems.en_US
dc.identifier.doi10.1109/ACCESS.2022.3185068
dc.identifier.endpage66796en_US
dc.identifier.issn2169-3536
dc.identifier.scopus2-s2.0-85133698329en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage66770en_US
dc.identifier.urihttps://doi.org/10.1109/ACCESS.2022.3185068
dc.identifier.urihttps://hdl.handle.net/20.500.12684/12981
dc.identifier.volume10en_US
dc.identifier.wosWOS:000818798300001en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorGüvenç, Uğur
dc.language.isoenen_US
dc.publisherIeee-Inst Electrical Electronics Engineers Incen_US
dc.relation.ispartofIeee Accessen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmz$2023V1Guncelleme$en_US
dc.subjectOptimization; Benchmark Testing; Costs; Resistance Heating; Statistical Analysis; Genetic Algorithms; Convergence; Optimization; Metaheuristic Search Algorithms; Fitness Distance Balance; Lshade; Energy Hub Economic Dispatchen_US
dc.subjectDifferential Evolution Algorithm; Particle Swarm Optimization; Flow; Model; Gasen_US
dc.titleFitness Distance Balance Based LSHADE Algorithm for Energy Hub Economic Dispatch Problemen_US
dc.typeArticleen_US

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