000			03008nam a22004815i 4500
001			978-0-387-24349-8
003			DE-He213
005			20250710083931.0
007			cr nn 008mamaa
008			100301s2005 xxu| s |||| 0|eng d
020			_a9780387243498 _a99780387243498
024	7		_a10.1007/b105200 _2doi
082	0	4	_a519.6 _223
100	1		_aSnyman, Jan A. _eauthor.
245	1	0	_aPractical Mathematical Optimization _h[recurso electrónico] : _bAn Introduction to Basic Optimization Theory and Classical and New Gradient-Based Algorithms / _cby Jan A. Snyman.
264		1	_aBoston, MA : _bSpringer US, _c2005.
300			_aXX, 258 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aApplied Optimization, _x1384-6485 ; _v97
505	0		_aLine Search Descent Methods for Unconstrained Minimization -- Standard Methods for Constrained Optimization -- New Gradient-Based Trajectory and Approximation Methods -- Example Problems -- Some Theorems.
520			_aThis book presents basic optimization principles and gradient-based algorithms to a general audience, in a brief and easy-to-read form without neglecting rigour. The work should enable the professional to apply optimization theory and algorithms to his own particular practical field of interest, be it engineering, physics, chemistry, or business economics. Most importantly, for the first time in a relatively brief and introductory work, due attention is paid to the difficulties-such as noise, discontinuities, expense of function evaluations, and the existence of multiple minima-that often unnecessarily inhibit the use of gradient-based methods. In a separate chapter on new gradient-based methods developed by the author and his coworkers, it is shown how these difficulties may be overcome without losing the desirable features of classical gradient-based methods. Audience It is intended that this book be used in senior- to graduate-level semester courses in optimization, as offered in mathematics, engineering, computer science, and operations research departments, and also to be useful to practising professionals in the workplace.
650		0	_aMATHEMATICS.
650		0	_aALGORITHMS.
650		0	_aNUMERICAL ANALYSIS.
650		0	_aMATHEMATICAL OPTIMIZATION.
650		0	_aOPERATIONS RESEARCH.
650	1	4	_aMATHEMATICS.
650	2	4	_aOPTIMIZATION.
650	2	4	_aALGORITHMS.
650	2	4	_aOPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING.
650	2	4	_aNUMERICAL ANALYSIS.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387243481
830		0	_aApplied Optimization, _x1384-6485 ; _v97
856	4	0	_uhttp://dx.doi.org/10.1007/b105200 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SMA
942			_2ddc _cER
999			_c56341 _d56341