Some Fundamental Properties of Successive Convex Relaxation Methods on LCP and Related Problems

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dc.creatorTuncel, Levent
dc.creatorKojima, Masakazu
dc.date2000-05-23
dc.date.accessioned2026-07-07T04:35:28Z
dc.date.available2026-07-07T04:35:28Z
dc.descriptionGeneral 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.description14 pages
dc.identifierhttps://arxiv.org/abs/math/0005229
dc.identifierhttp://arxiv.org/abs/math/0005229
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/59263
dc.subjectCombinatorics
dc.titleSome Fundamental Properties of Successive Convex Relaxation Methods on LCP and Related Problems
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