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An overview on conjugate gradient methods for optimization, extensions and applications

dc.contributor.authorAguilar Mendoza, Hans Steven
dc.contributor.authorPapa Quiroz, Erik Alex
dc.contributor.authorCano Lengua, Miguel Angel
dc.date.accessioned2023-10-17T14:23:30Z
dc.date.available2023-10-17T14:23:30Z
dc.date.issued2021-11-30
dc.identifier.citationAguilar, H., Papa, E., & Cano, M. (2021). An overview on conjugate gradient methods for optimization, extensions and applications. Proceedings of the 2021 IEEE Engineering International Research Conference, EIRCON 2021. https://doi.org/10.1109/EIRCON52903.2021.9613264es_PE
dc.identifier.other.es_PE
dc.identifier.urihttps://hdl.handle.net/11537/34513
dc.descriptionEl texto completo de este trabajo no está disponible en el Repositorio Académico UPN por restricciones de la casa editorial donde ha sido publicado.
dc.description.abstractThis paper aims to identify the current state of the art of the latest research related to Conjugate Gradient (CG) methods for unconstrained optimization through a systematic literature review according to the methodology proposed by Kitchenham and Charter, to answer the following research questions: Q1: In what research areas are the conjugate gradient method used? Q2: Can Dai-Yuan conjugate gradient algorithm be effectively applied in portfolio selection? Q3: Have conjugate gradient methods been used to develop large-scale numerical results? Q4: What conjugate gradient methods have been used to minimize quasiconvex or nonconvex functions? We obtain useful results to extend the applications of the CG methods, develop efficient algorithms, and continue studying theoretical convergence results.es_PE
dc.formatapplication/pdfes_PE
dc.language.isospaes_PE
dc.publisherIEEE Engineering International Research Conference (EIRCON)es_PE
dc.rightsinfo:eu-repo/semantics/closedAccesses_PE
dc.sourceUniversidad Privada del Nortees_PE
dc.sourceRepositorio Institucional - UPNes_PE
dc.subjectMétodos de gradiente conjugado (CG)es_PE
dc.subjectArte y métodos de gradiente conjugadoes_PE
dc.subjectConjugate Gradient (CG) Methodses_PE
dc.titleAn overview on conjugate gradient methods for optimization, extensions and applicationses_PE
dc.typeinfo:eu-repo/semantics/conferenceObjectes_PE
dc.publisher.countryPEes_PE
dc.identifier.journalProceedings of the 2021 IEEE Engineering International Research Conference, EIRCON 2021es_PE
dc.description.peer-reviewConference Paperes_PE
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#2.11.04es_PE
dc.description.sedeComases_PE
dc.identifier.doihttps://doi.org/10.1109/EIRCON52903.2021.9613264


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