Lagrangian duality underlies many efficient algorithms for convex minimization problems. A key ingredient is strong duality. Lagrangian relaxation also provides lower bounds for non-convex problems, where the quality of the lower bound depends on the duality gap. Quadratically constrained quadratic
✦ LIBER ✦
Characterization of the smoothness and curvature of a marginal function for a trust-region problem
✍ Scribed by David A. Andrews; Luís N. Vicente
- Publisher
- Springer-Verlag
- Year
- 1999
- Tongue
- English
- Weight
- 165 KB
- Volume
- 84
- Category
- Article
- ISSN
- 0025-5610
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