Numerical methods for large-scale non-convex quadratic programming

ePubs

The open archive for STFC research publications

Persistent URL	http://purl.org/net/epubs/work/29567
Record Status	Checked
Record Id	29567
Title	Numerical methods for large-scale non-convex quadratic programming
Contributors	NIM Gould (CCLRC Rutherford Appleton Lab.), PL Toint
Abstract	We consider numerical methods for finding (weak) second-order critical points for large-scale non-convex quadratic programming problems. We describe two new methods. The first is of the active-set variety. Although convergent from any starting point, it is intended primarily for the case where a good estimate of the optimal active set can be predicted. The second is an interior-point trust-region type, and has proved capable of solving problems involving up to half a million unknowns and constraints. The results of comparative tests on a large set of convex and non-convex quadratic programming examples are given.
Organisation	CCLRC
Keywords
Funding Information
Related Research Object(s):	40520 , 40522
Licence Information:
Language	English (EN)

Type	Details	URI(s)	Local file(s)	Year
Report	RAL Technical Reports RAL-TR-2001-017. 2001.		RAL-TR-2001-017.pdf	2001