Abstract
For the problem of minimizing the sum of Euclidean norms (MSN), most existing quadratically convergent algorithms require a strict complementarity assumption. However, this assumption is not satisfied for a number of MSN problems. In this paper, we present a globally and quadratically convergent algorithm for the MSN problem. In particular, the quadratic convergence result is obtained without assuming strict complementarity. Examples without strictly complementary solutions are given to show that our algorithm can indeed achieve quadratic convergence. Preliminary numerical results are reported.
Original language | English |
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Pages (from-to) | 357-377 |
Number of pages | 21 |
Journal | Journal of Optimization Theory and Applications |
Volume | 119 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1 Nov 2003 |
Externally published | Yes |
Keywords
- Quadratic convergence
- Strict complementarity
- Sum of norms
ASJC Scopus subject areas
- Control and Optimization
- Management Science and Operations Research
- Applied Mathematics