Augmented grasshopper optimization algorithm by differential evolution: a power scheduling application in smart homes

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dc.authorid0000-0002-2131-6368en_US
dc.contributor.authorZiadeh, Ahmad
dc.contributor.authorAbualigah, Laith
dc.contributor.authorAbd Elaziz, Mohamed
dc.contributor.authorBatur Şahin, Canan
dc.contributor.authorAlmazroi, Abdulwahab Ali
dc.contributor.authorOmari, Mahmoud
dc.date.accessioned2021-09-21T08:19:37Z
dc.date.available2021-09-21T08:19:37Z
dc.date.issued2021en_US
dc.departmentMTÖ Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Yazılım Mühendisliği Bölümüen_US
dc.description.abstractWith the increasing number of electricity consumers, production, distribution, and consumption problems of produced energy have appeared. This paper proposed an optimization method to reduce the peak demand using smart grid capabilities. In the proposed method, a hybrid Grasshopper Optimization Algorithm (GOA) with the self-adaptive Differential Evolution (DE) is used, called HGOA. The proposed method takes advantage of the global and local search strategies from Differential Evolution and Grasshopper Optimization Algorithm. Experimental results are applied in two scenarios; the first scenario has universal inputs and several appliances. The second scenario has an expanded number of appliances. The results showed that the proposed method (HGOA) got better power scheduling arrangements and better performance than other comparative algorithms using the classical benchmark functions. Moreover, according to the computational time, it runs in constant execution time as the population is increased. The proposed method got 0.26?% enhancement compared to the other methods. Finally, we found that the proposed HGOA always got better results than the original method in the worst cases and the best cases.en_US
dc.identifier.citationZiadeh, A., Abualigah, L., Abd Elaziz, M., Şahin, C. B., Almazroi, A. A., & Omari, M. (2021). Augmented grasshopper optimization algorithm by differential evolution: a power scheduling application in smart homes. Multimedia Tools and Applications, 1-29.en_US
dc.identifier.doi10.1007/s11042-021-11099-1
dc.identifier.endpage29en_US
dc.identifier.issn1380-7501en_US
dc.identifier.issn1573-7721en_US
dc.identifier.scopus2-s2.0-85109018707en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1en_US
dc.identifier.urihttps://doi.org/10.1007/s11042-021-11099-1
dc.identifier.urihttps://hdl.handle.net/20.500.12899/433
dc.identifier.wosWOS:000668056500002en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorBatur Şahin, Canan
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofMultimedia Tools and Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.subjectHybrid methoden_US
dc.subjectGrasshopper optimization algorithmen_US
dc.subjectDifferential evolutionen_US
dc.subjectPower schedulingen_US
dc.subjectSmart homesen_US
dc.subjectSmart griden_US
dc.titleAugmented grasshopper optimization algorithm by differential evolution: a power scheduling application in smart homesen_US
dc.typeArticleen_US

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