000			02878nam a22003615i 4500
001			278341
003			MX-SnUAN
005			20160429153859.0
007			cr nn 008mamaa
008			150903s2005 xxu| o |||| 0|eng d
020			_a9780387243498 _9978-0-387-24349-8
024	7		_a10.1007/b105200 _2doi
035			_avtls000330058
039		9	_a201509031109 _bVLOAD _c201405070456 _dVLOAD _c201401311328 _dstaff _c201401311152 _dstaff _y201401291446 _zstaff _wmsplit0.mrc _x478
050		4	_aQA402.5-402.6
100	1		_aSnyman, Jan A. _eautor _9301909
245	1	0	_aPractical Mathematical Optimization : _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 páginas, _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aApplied Optimization, _x1384-6485 ; _v97
500			_aSpringer eBooks
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.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9780387243481
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/b105200 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942			_c14
999			_c278341 _d278341