000			03633nam a22004815i 4500
001			978-0-387-84806-8
003			DE-He213
005			20251006084422.0
007			cr nn 008mamaa
008			100301s2009 xxu| s |||| 0|eng d
020			_a9780387848068
020			_a99780387848068
024	7		_a10.1007/b138610 _2doi
100	1		_aDostál, Zdenek. _eauthor.
245	1	0	_aOptimal Quadratic Programming Algorithms _h[electronic resource] : _bWith Applications to Variational Inequalities / _cby Zdenek Dostál.
264		1	_aBoston, MA : _bSpringer US, _c2009.
300			_aXVIII, 284 p. 55 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringer Optimization and Its Applications, _x1931-6828 ; _v23
505	0		_aI Background -- Linear Algebra -- Optimization -- II Algorithms -- Conjugate Gradients for Unconstrained Minimization -- Equality Constrained Minimization -- Bound Constrained Minimization -- Bound and Equality Constrained Minimization -- III Applications to Variational Inequalities -- Solution of a Coercive Variational Inequality by FETI-DP Method -- Solution of a Semicoercive Variational Inequality by TFETI Method.
520			_aSolving optimization problems in complex systems often requires the implementation of advanced mathematical techniques. Quadratic programming (QP) is one technique that allows for the optimization of a quadratic function in several variables in the presence of linear constraints. QP problems arise in fields as diverse as electrical engineering, agricultural planning, and optics. Given its broad applicability, a comprehensive understanding of quadratic programming is a valuable resource in nearly every scientific field. Optimal Quadratic Programming Algorithms presents recently developed algorithms for solving large QP problems. The presentation focuses on algorithms which are, in a sense optimal, i.e., they can solve important classes of problems at a cost proportional to the number of unknowns. For each algorithm presented, the book details its classical predecessor, describes its drawbacks, introduces modifications that improve its performance, and demonstrates these improvements through numerical experiments. This self-contained monograph can serve as an introductory text on quadratic programming for graduate students and researchers. Additionally, since the solution of many nonlinear problems can be reduced to the solution of a sequence of QP problems, it can also be used as a convenient introduction to nonlinear programming. The reader is required to have a basic knowledge of calculus in several variables and linear algebra.
650		0	_aMATHEMATICS.
650		0	_aNUMERICAL ANALYSIS.
650		0	_aMATHEMATICAL OPTIMIZATION.
650		0	_aOPERATIONS RESEARCH.
650		0	_aENGINEERING MATHEMATICS.
650	1	4	_aMATHEMATICS.
650	2	4	_aNUMERICAL ANALYSIS.
650	2	4	_aAPPL.MATHEMATICS/COMPUTATIONAL METHODS OF ENGINEERING.
650	2	4	_aOPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING.
650	2	4	_aCALCULUS OF VARIATIONS AND OPTIMAL CONTROL; OPTIMIZATION.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387848051
830		0	_aSpringer Optimization and Its Applications, _x1931-6828 ; _v23
856	4	0	_uhttp://dx.doi.org/10.1007/b138610 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SMA
942			_2ddc _cER
999			_c59212 _d59212