A robust algorithm for quadratic optimization under quadratic constraints
Source: Journal of Global Optimization, Volume 37, Number 4, April 2007 , pp. 557-569(13)
Abstract:Most existing methods of quadratically constrained quadratic optimization actually solve a refined linear or convex relaxation of the original problem. It turned out, however, that such an approach may sometimes provide an infeasible solution which cannot be accepted as an approximate optimal solution in any reasonable sense. To overcome these limitations a new approach is proposed that guarantees a more appropriate approximate optimal solution which is also stable under small perturbations of the constraints.
Document Type: Research article
Publication date: 2007-04-01