000			03748nam a22004695i 4500
001			u370201
003			SIRSI
005			20160812080019.0
007			cr nn 008mamaa
008			100803s2010 xxu| s |||| 0|eng d
020			_a9780387684079 _9978-0-387-68407-9
040			_cMX-MeUAM
050		4	_aQA402.5-402.6
082	0	4	_a519.6 _223
100	1		_aGüler, Osman. _eauthor.
245	1	0	_aFoundations of Optimization _h[recurso electrónico] / _cby Osman Güler.
264		1	_aNew York, NY : _bSpringer New York, _c2010.
300			_aXVIII, 442 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aGraduate Texts in Mathematics, _x0072-5285 ; _v258
505	0		_aDifferential Calculus -- Unconstrained Optimization -- Variational Principles -- Convex Analysis -- Structure of Convex Sets and Functions -- Separation of Convex Sets -- Convex Polyhedra -- Linear Programming -- Nonlinear Programming -- Structured Optimization Problems -- Duality Theory and Convex Programming -- Semi-infinite Programming -- Topics in Convexity -- Three Basic Optimization Algorithms.
520			_aThe book gives a detailed and rigorous treatment of the theory of optimization (unconstrained optimization, nonlinear programming, semi-infinite programming, etc.) in finite-dimensional spaces. The fundamental results of convexity theory and the theory of duality in nonlinear programming and the theories of linear inequalities, convex polyhedra, and linear programming are covered in detail. Over two hundred, carefully selected exercises should help the students master the material of the book and give further insight. Some of the most basic results are proved in several independent ways in order to give flexibility to the instructor. A separate chapter gives extensive treatments of three of the most basic optimization algorithms (the steepest-descent method, Newton’s method, the conjugate-gradient method). The first chapter of the book introduces the necessary differential calculus tools used in the book. Several chapters contain more advanced topics in optimization such as Ekeland’s epsilon-variational principle, a deep and detailed study of separation properties of two or more convex sets in general vector spaces, Helly’s theorem and its applications to optimization, etc. The book is suitable as a textbook for a first or second course in optimization at the graduate level. It is also suitable for self-study or as a reference book for advanced readers. The book grew out of author’s experience in teaching a graduate level one-semester course a dozen times since 1993. Osman Guler is a Professor in the Department of Mathematics and Statistics at University of Maryland, Baltimore County. His research interests include mathematical programming, convex analysis, complexity of optimization problems, and operations research.
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.
650	2	4	_aApplications of Mathematics.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387344317
830		0	_aGraduate Texts in Mathematics, _x0072-5285 ; _v258
856	4	0	_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-0-387-68407-9
596			_a19
942			_cLIBRO_ELEC
999			_c198081 _d198081