Volume 40, Number 3, July-September 2006
|Page(s)||253 - 265|
|Published online||08 November 2006|
On semidefinite bounds for maximization of a non-convex quadratic objective over the l1 unit ball
Department of Industrial Engineering,Bilkent University, 06533 Ankara, Turkey; firstname.lastname@example.org
2 School of Mathematical Sciences, Tel-Aviv University, Ramat-Aviv 69978, Israel; email@example.com
Accepted: 26 January 2006
We consider the non-convex quadratic maximization problem subject to the l1 unit ball constraint. The nature of the l1 norm structure makes this problem extremely hard to analyze, and as a consequence, the same difficulties are encountered when trying to build suitable approximations for this problem by some tractable convex counterpart formulations. We explore some properties of this problem, derive SDP-like relaxations and raise open questions.
Key words: Non-convex quadratic optimization / L1-norm constraint / semidefinite programming relaxation / duality.
© EDP Sciences, 2006
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