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|Title:||A smoothing newton-type algorithm of stronger convergence for the quadratically constrained convex quadratic programming||Authors:||Huang, Z.-H.
Smoothing Newton method
|Issue Date:||Oct-2006||Citation:||Huang, Z.-H., Sun, D., Zhao, G. (2006-10). A smoothing newton-type algorithm of stronger convergence for the quadratically constrained convex quadratic programming. Computational Optimization and Applications 35 (2) : 199-237. ScholarBank@NUS Repository. https://doi.org/10.1007/s10589-006-6512-7||Abstract:||In this paper we propose a smoothing Newton-type algorithm for the problem of minimizing a convex quadratic function subject to finitely many convex quadratic inequality constraints. The algorithm is shown to converge globally and possess stronger local superlinear convergence. Preliminary numerical results are also reported. © 2006 Springer Science + Business Media, LLC.||Source Title:||Computational Optimization and Applications||URI:||http://scholarbank.nus.edu.sg/handle/10635/102765||ISSN:||09266003||DOI:||10.1007/s10589-006-6512-7|
|Appears in Collections:||Staff Publications|
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