MARC Record from marc_columbia

LEADER: 04337cam a2200745 i 4500
001 15632867
005 20210918231127.0
006 m o d
007 cr |n|||||||||
008 200929s2020 flu ob 001 0 eng d
035 $a(OCoLC)on1198016973
035 $a(NNC)15632867
040 $aYDX$beng$erda$epn$cYDX$dYDX$dN$T$dUKMGB$dEBLCP$dOCLCO$dUKAHL$dTYFRS$dWAU
015 $aGBC072677$2bnb
016 7 $a019811560$2Uk
019 $a1197870705
020 $a9781000220339$q(electronic bk.)
020 $a1000220338$q(electronic bk.)
020 $a9781000220131$q(PDF ebook)
020 $a1000220133
020 $a9781000220230$q(Mobipocket ebook)
020 $a1000220230
020 $a9781003042518$q(ebook)
020 $a1003042511
020 $z9780367487287
020 $z0367487284
024 7 $a10.1201/9781003042518$2doi
035 $a(OCoLC)1198016973$z(OCoLC)1197870705
037 $a9781000220339$bIngram Content Group
037 $a9781003042518$bTaylor & Francis
050 4 $aQA402.5
072 7 $aMAT$x003000$2bisacsh
072 7 $aMAT$x004000$2bisacsh
072 7 $aMAT$x013000$2bisacsh
072 7 $aUMB$2bicssc
082 04 $a519.7$223
049 $aZCUA
100 1 $aYang, Yaguang,$eauthor.
245 10 $aArc-search techniques for interior-point methods /$cYaguang Yang.
264 1 $aBoca Raton :$bCRC Press ;$bTaylor & Francis Group,$c[2020]
300 $a1 online resource (x, 306 pages) :$billustrations
336 $atext$2rdacontent
336 $astill image$2rdacontent
337 $acomputer$2rdamedia
338 $aonline resource$2rdacarrier
504 $aIncludes bibliographical references and index.
505 0 $aA 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( n̄L) 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.
520 $a"This book discusses one of the most recent developments in interior-point methods, the arc-search techniques. Introducing these techniques result in an efficient interior-point algorithm with the lowest polynomial bound, which solves a long-standing issue of the interior-point methods in linear programming, i.e., the algorithm with the best polynomial bound is the least efficient and the most efficient interior-point algorithm cannot be proved to converge. The book also covers important results since 1990s and the extensions of the arc-search techniques to the general optimization problems, such as convex quadratic programming, linear complementarity problem, and semi-definite programming"--$cProvided by publisher.
545 0 $aYaguang Yang received a BSc (1982) and a MSc (1985) from Huazhong University of Science and Technology, China. From 1985 to 1990, he was a lecturer at Zhejiang University in China. In 1996, he received his PhD from the Department of Electrical and Computer Engineering at the University of Maryland, College Park. He proposed and developed arc-search techniques for interior-point methods. He is currently with the US Nuclear Regulatory Commission.
588 0 $aOnline resource; title from PDF title page (viewed September 9, 2021).
650 0 $aInterior-point methods.
650 0 $aLinear programming.
650 0 $aComputer algorithms.
650 7 $aComputer algorithms.$2fast$0(OCoLC)fst00872010
650 7 $aInterior-point methods.$2fast$0(OCoLC)fst00976414
650 7 $aLinear programming.$2fast$0(OCoLC)fst00999090
650 7 $aMATHEMATICS / Applied$2bisacsh
650 7 $aMATHEMATICS / Arithmetic$2bisacsh
650 7 $aMATHEMATICS / Graphic Methods$2bisacsh
655 0 $aElectronic books.
655 4 $aElectronic books.
776 08 $iPrint version:$z9781000220339
776 08 $iPrint version:$z9780367487287$z0367487284$w(DLC) 2020013760$w(OCoLC)1156436895
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio15632867$zTaylor & Francis eBooks
852 8 $blweb$hEBOOKS