Two trust-region methods for systems of mixed nonlinear equalities, general inequalities and simple bounds are proposed. The first method is based on a Gauss–Newton model, the second one is based on a regularized Gauss–Newton model and results to be a Levenberg–Marquardt method. The globalization strategy uses affine scaling matrices arising in bound-constrained optimization. Global convergence results are established and quadratic rate is achieved under an error bound assumption. The numerical efficiency of the new methods is experimentally studied.

Trust-region quadratic methods for nonlinear systems of mixed equalities and inequalities / M.Macconi; B.Morini; M.Porcelli. - In: APPLIED NUMERICAL MATHEMATICS. - ISSN 0168-9274. - STAMPA. - 59:(2009), pp. 859-876. [10.1016/j.apnum.2008.03.028]

Trust-region quadratic methods for nonlinear systems of mixed equalities and inequalities

MACCONI, MARIA;MORINI, BENEDETTA;M. Porcelli
2009

Abstract

Two trust-region methods for systems of mixed nonlinear equalities, general inequalities and simple bounds are proposed. The first method is based on a Gauss–Newton model, the second one is based on a regularized Gauss–Newton model and results to be a Levenberg–Marquardt method. The globalization strategy uses affine scaling matrices arising in bound-constrained optimization. Global convergence results are established and quadratic rate is achieved under an error bound assumption. The numerical efficiency of the new methods is experimentally studied.
2009
59
859
876
M.Macconi; B.Morini; M.Porcelli
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/315096
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