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Algorithm for solutions of nonlinear equations of strongly monotone type and applications to convex minimization and variational inequality problems

dc.contributor.authorAibinu, Mathew O.en_US
dc.contributor.authorThakur, Surendra C.en_US
dc.contributor.authorMoyo, Sibusisoen_US
dc.date.accessioned2021-03-05T09:27:41Z
dc.date.available2021-03-05T09:27:41Z
dc.date.issued2020-08-01
dc.date.updated2020-08-09T08:26:30Z
dc.description.abstractReal-life problems are governed by equations which are nonlinear in nature. Nonlinear equations occur in modeling problems, such as minimizing costs in industries and minimizing risks in businesses. A technique which does not involve the assumption of existence of a real constant whose calculation is unclear is used to obtain a strong convergence result for nonlinear equations of (p, {\eta})-strongly monotone type, where {\eta} > 0, p > 1. An example is presented for the nonlinear equations of (p, {\eta})-strongly monotone type. As a consequence of the main result, the solutions of convex minimization and variational inequality problems are obtained. This solution has applications in other fields such as engineering, physics, biology, chemistry, economics, and game theory.en_US
dc.format.extent11 p.en_US
dc.identifier.citationAbinu, M.O., Thakur, S.C., Moyo, S. 2020. Algorithm for solutions of nonlinear equations of strongly monotone type and applications to convex minimization and variational inequality problems. Abstract and Applied Analysis, 2020: 1-11. doi:10.1155/2020/6579720en_US
dc.identifier.doihttps://doi.org/10.1155/2020/6579720
dc.identifier.issn1085-3375
dc.identifier.issn1687-0409 (Online)
dc.identifier.urihttp://hdl.handle.net/10321/3545
dc.language.isoenen_US
dc.publisherHindawi Limiteden_US
dc.relation.ispartofAbstract and Applied Analysisen_US
dc.subjectApplied mathematicsen_US
dc.subjectPure mathematicsen_US
dc.titleAlgorithm for solutions of nonlinear equations of strongly monotone type and applications to convex minimization and variational inequality problemsen_US
dc.typeArticleen_US
local.sdgSDG10

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