Name
Title | ||
|---|---|---|
Some Fundamental Properties of Successive Convex Relaxation Methods on LCP and Related Problems |
Abstract | ||
|---|---|---|
General successive convex relaxation methods (SRCMs) can be used to compute the convex hull of any compact set, in an Euclidean space, described by a system of quadratic inequalities and a compact convex set. Linear complementarity problems (LCPs) make an interesting and rich class of structured nonconvex optimization problems. In this paper, we study a few of the specialized lift-and-project methods and some of the possible ways of applying the general SCRMs to LCPs and related problems. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1023/A:1020300717650 | Journal of Global Optimization |
Keywords | Field | DocType |
Nonconvex quadratic optimization,Linear complementarity problem,Semidefinite programming,Global optimization,SDP relaxation,Convex relaxation,Lift-and-project procedures | Mathematical optimization,Convex combination,Mathematical analysis,Convex set,Convex hull,Subderivative,Convex polytope,Proper convex function,Convex optimization,Convex analysis,Mathematics | Journal |
Volume | Issue | ISSN |
24 | 3 | 1573-2916 |
Citations | PageRank | References |
4 | 0.56 | 8 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Masakazu Kojima | 1 | 1603 | 222.51 |
| Levent Tunç/el | 2 | 4 | 0.56 |