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Quasi-Newton Methods for Solving Nonlinear Programming Problems

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dc.contributor.author MORARU, V.
dc.date.accessioned 2020-12-18T10:10:09Z
dc.date.available 2020-12-18T10:10:09Z
dc.date.issued 1995
dc.identifier.citation MORARU, V. Quasi-Newton Methods for Solving Nonlinear Programming Problems. In: Computer Science Journal of Moldova. 1995, Vol 3, nr. 3(9), pp.263-277. ISSN 1561-4042. en_US
dc.identifier.uri http://repository.utm.md/handle/5014/12195
dc.description.abstract In the present paper the problem of constrained equality optimization is reduced to sequential solving a series of problems of quadratic programming. The Hessian of the Lagrangian is approximated by a sequence of symmetric positive definite matrices. The matrix approximation is updated at every iteration by a Gram- Schmidt modified algorithm. We establish that methods is locally convergent and the sequence {xk}converges to the solution a two-step superlinear rate. en_US
dc.language.iso en en_US
dc.publisher Institute of Mathematics and Computer Science en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject nonlinear programming en_US
dc.title Quasi-Newton Methods for Solving Nonlinear Programming Problems en_US
dc.type Article en_US


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