Symmetry in RLT-type relaxations for the quadratic assignment and standard quadratic optimization problems
โ Scribed by de Klerk, Etienne; -Nagy, Marianna E.; Sotirov, Renata; Truetsch, Uwe
- Book ID
- 122258088
- Publisher
- Elsevier Science
- Year
- 2014
- Tongue
- English
- Weight
- 556 KB
- Volume
- 233
- Category
- Article
- ISSN
- 0377-2217
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
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
This Book Constitutes The Refereed Proceedings Of The Second International Conference On Evolutionary Multi-criterion Optimization, Emo 2003, Held In Faro, Portugal, In April 2003. The 56 Revised Full Papers Presented Were Carefully Reviewed And Selected From A Total Of 100 Submissions. The Papers A