Arc-search techniques for interior-point methods / Yaguang Yang, Office of Research, US Nuclear Regulatory Commission, Rockville, Maryland, USA.

Author/creator Yang, Yaguang
Format Electronic
Publication InfoBoca Raton : CRC Press/Taylor & Francis Group, [2020]
Descriptionx, 306 pages ; 24 cm
Supplemental ContentFull text available from Taylor & Francis eBooks
Subjects

Contents A potential-reduction algorithm for LP -- Feasible path-following algorithms for LP -- Infeasible interior-point method algorithms for LP -- A feasible arc-search algorithm for LP -- A MTY-type infeasible arc-search Algorithm for LP -- A Mehrotra-type infeasible arc-search algorithm for LP -- An O( n¿¿L) infeasible arc-search algorithm for LP -- An arc-search algorithm for convex quadratic programming -- An arc-search algorithm for QP with box constraints -- An arc-search algorithm for LCP -- An arc-search algorithm for semidefinite programming.
Abstract "This book discusses one of the most recent developments in interior-point methods, the arc-search techniques. Introducing these techniques result in an efficient interior-point algorithm with the lowest polynomial bound, which solves a long-standing issue of the interior-point methods in linear programming, i.e., the algorithm with the best polynomial bound is the least efficient and the most efficient interior-point algorithm cannot be proved to converge. The book also covers important results since 1990s and the extensions of the arc-search techniques to the general optimization problems, such as convex quadratic programming, linear complementarity problem, and semi-definite programming"-- Provided by publisher.
Bibliography noteIncludes bibliographical references and index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
LCCN 2020013760
ISBN9780367487287 (hardcover)

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