000			03778nam a22004455i 4500
001			978-0-387-78723-7
003			DE-He213
005			20251006084419.0
007			cr nn 008mamaa
008			100301s2008 xxu| s |||| 0|eng d
020			_a9780387787237
020			_a99780387787237
024	7		_a10.1007/978-0-387-78723-7 _2doi
100	1		_aBartholomew-Biggs, Michael. _eauthor.
245	1	0	_aNonlinear Optimization with Engineering Applications _h[electronic resource] / _cby Michael Bartholomew-Biggs.
264		1	_aBoston, MA : _bSpringer US, _c2008.
300			_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 ; _v19
505	0		_aIntroducing Optimization -- One-variable Optimization -- Applications in n Variables -- n-Variable Unconstrained Optimization -- Direct Search Methods -- Computing Derivatives -- The Steepest Descent Method -- Weak Line Searches and Convergence -- Newton and Newton-like Methods -- Quasi-Newton Methods -- Conjugate Gradient Methods -- ASummary of Unconstrained Methods -- Optimization with Restrictions -- Larger-Scale Problems -- Global Unconstrained Optimization -- Equality Constrained Optimization -- Linear Equality Constraints -- Penalty Function Methods -- Sequential Quadratic Programming -- Inequality Constrained Optimization -- Extending Equality Constraint Methods -- Barrier Function Methods -- Interior Point Methods -- A Summary of Constrained Methods -- The OPTIMA Software.
520			_aThis textbook examines a broad range of problems in science and engineering, describing key numerical methods applied to real life. The case studies presented are in such areas as data fitting, vehicle route planning and optimal control, scheduling and resource allocation, sensitivity calculations and worst-case analysis. Among the main topics covered: * one-variable optimization - optimality conditions, direct search and gradient * unconstrained optimization in n variables - solution methods including Nelder and Mead simplex, steepest descent, Newton, Gauss-Newton, and quasi-Newton techniques, trust regions and conjugate gradients * constrained optimization in n variables - solution methods including reduced-gradients, penalty and barrier methods, sequential quadratic programming, and interior point techniques * an introduction to global optimization * an introduction to automatic differentiation Chapters are self-contained with exercises provided at the end of most sections. Nonlinear Optimization with Engineering Applications is ideal for self-study and classroom use in engineering courses at the senior undergraduate or graduate level. The book will also appeal to postdocs and advanced researchers interested in the development and use of optimization algorithms. Also by the author: Nonlinear Optimization with Financial Applications, ISBN: 978-1-4020-8110-1, (c)2005, Springer.
650		0	_aMATHEMATICS.
650		0	_aMATHEMATICAL OPTIMIZATION.
650		0	_aOPERATIONS RESEARCH.
650	1	4	_aMATHEMATICS.
650	2	4	_aOPTIMIZATION.
650	2	4	_aCALCULUS OF VARIATIONS AND OPTIMAL CONTROL; OPTIMIZATION.
650	2	4	_aOPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387787220
830		0	_aSpringer Optimization and Its Applications, _x1931-6828 ; _v19
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-78723-7 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SMA
942			_2ddc _cER
999			_c59104 _d59104