Minimize the cost function in multiple objective optimization by using NSGA-II

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dc.contributor.authorSafi, Hayder H.
dc.contributor.authorMohammed, Tareq Abed
dc.contributor.authorAl-Qubbanchi, Z.F.
dc.date.accessioned2021-05-15T12:50:02Z
dc.date.available2021-05-15T12:50:02Z
dc.date.issued2019
dc.departmentMühendislik ve Doğa Bilimleri Fakültesi, Temel Bilimler Bölümüen_US
dc.descriptionArtificial Intelligence on Fashion and Textiles Conference, AIFT 2018 -- 27 June 2018 through 29 June 2018 -- -- 219689
dc.description.abstractThis study proposes a new framework to minimize the cost function of multi-objective optimization problems by using NSGA-II in economic environments. For multi-objective improvements, the most generally used developmental algorithms such as NSGA-II, SPEA2 and PESA-II can be utilized. The economical optimization framework includes destinations, requirements, and parameters which continuously can change with time. The minimization of the cost function issue is one of the most important issues as in the case of stationary optimization problems. In this paper, we propose a framework that can possibly reduce the high cost of all functions that used in economic environments. Our algorithm uses a set of linear equations as inputs which depend on multi-objective algorithm that based on a Non-Dominated Sorting Genetic Algorithm (NSGA-II). The results of our experimental study show that the proposed framework can efficiently be used to reduce the cost and time of optimizing the economical problems. © Springer Nature Switzerland AG 2019.en_US
dc.identifier.doi10.1007/978-3-319-99695-0_18
dc.identifier.endpage152en_US
dc.identifier.isbn9783319996943
dc.identifier.issn2194-5357
dc.identifier.scopus2-s2.0-85055684648
dc.identifier.scopusqualityN/A
dc.identifier.startpage145en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-319-99695-0_18
dc.identifier.urihttps://hdl.handle.net/20.500.12939/1171
dc.identifier.volume849en_US
dc.indekslendigikaynakScopus
dc.institutionauthorSafi, Hayder H.
dc.institutionauthorMohammed, Tareq Abed
dc.language.isoen
dc.publisherSpringer Verlagen_US
dc.relation.ispartofAdvances in Intelligent Systems and Computing
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCost Functionen_US
dc.subjectNSGA-II Multi-Objective Problemen_US
dc.subjectVector Optimizationen_US
dc.subjectVehicle Suspension Systemen_US
dc.titleMinimize the cost function in multiple objective optimization by using NSGA-II
dc.typeConference Object

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