Abstract
We consider a case of the convex feasibility problem where the set is defined by an infinite number of certain strongly convex self-concordant inequalities. At each iteration, the algorithm adds a self-concordant cut through an approximate analytic center of the current set of localization until a feasible point is found. We show that the algorithm is a fully polynomial approximation scheme.
This research is supported by the Natural Sciences and Engineering Research Council of Canada, grant number OPG0004152 and by the FCAR of Quebec.
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© 2001 Kluwer Academic Publishers
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Mokhtarian, F.S., Goffin, JL. (2001). An Analytic Center Self-Concordant Cut Method for the Convex Feasibility Problem. In: Hadjisavvas, N., Pardalos, P.M. (eds) Advances in Convex Analysis and Global Optimization. Nonconvex Optimization and Its Applications, vol 54. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-0279-7_24
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DOI: https://doi.org/10.1007/978-1-4613-0279-7_24
Publisher Name: Springer, Boston, MA
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