Name
Abstract | ||
|---|---|---|
Finding feasible points for which the proof succeeds is a critical issue in safe Branch and Bound algorithms which handle continuous problems. In this paper, we introduce a new strategy to compute very accurate approximations of feasible points. This strategy takes advantage of the Newton method for under-constrained systems of equations and inequalities. More precisely, it exploits the optimal solution of a linear relaxation of the problem to compute efficiently a promising upper bound. First experiments on the Coconuts benchmarks demonstrate that this approach is very effective. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-85958-1_49 | Clinical Orthopaedics and Related Research |
Keywords | DocType | Volume |
linear relaxation,continuous problem,newton method,critical issue,coconuts benchmarks,upper bounding process,bound algorithm,optimal solution,new strategy,accurate approximation,feasible point,safe branch,branch and bound algorithm,global optimization,numerical analysis,upper bound,local search | Conference | abs/0807.2382 |
ISSN | Citations | PageRank |
0302-9743 | 4 | 0.44 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexandre Goldsztejn | 1 | 161 | 21.42 |
| Yahia Lebbah | 2 | 115 | 19.34 |
| Claude Michel | 3 | 107 | 10.57 |
| Michel Rueher | 4 | 613 | 59.81 |