Please use this identifier to cite or link to this item:
|Title:||A smoothing newton-type algorithm of stronger convergence for the quadratically constrained convex quadratic programming|
Smoothing Newton method
|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|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Jul 16, 2018
WEB OF SCIENCETM
checked on Jun 26, 2018
checked on Jun 22, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.