Some fundamental properties of successive convex relaxation methods on LCP and related problems
| dc.creator | Kojima, Masakazu | |
| dc.creator | Tuncel, Levent | |
| dc.date | 1999-05-01 | |
| dc.date.accessioned | 2026-07-07T05:29:19Z | |
| dc.date.available | 2026-07-07T05:29:19Z | |
| dc.description | 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 which is not very complicated. 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. | |
| dc.identifier | https://arxiv.org/abs/math/9905199 | |
| dc.identifier | http://arxiv.org/abs/math/9905199 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/78589 | |
| dc.subject | Optimization and Control | |
| dc.subject | Metric Geometry | |
| dc.title | Some fundamental properties of successive convex relaxation methods on LCP and related problems | |
| dc.type | text |