000			a
999			_c33865 _d33865
008			250422b xxu||||| |||| 00| 0 eng d
020			_a9781493937110
082			_a519.6 _bNOC
100			_aNocedal, Jorge
245			_aNumerical optimization
250			_a2nd ed.
260			_bSpringer, _c2006 _aNew York :
300			_axxii, 664 p. ; _bill. (some col.), _c24 cm.
365			_b49.99 _c€ _d97.70
504			_aIncludes bibliographical references and index.
520			_aNumerical Optimization presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. It responds to the growing interest in optimization in engineering, science, and business by focusing on the methods that are best suited to practical problems. For this new edition the book has been thoroughly updated throughout. There are new chapters on nonlinear interior methods and derivative-free methods for optimization, both of which are used widely in practice and the focus of much current research. Because of the emphasis on practical methods, as well as the extensive illustrations and exercises, the book is accessible to a wide audience. It can be used as a graduate text in engineering, operations research, mathematics, computer science, and business. It also serves as a handbook for researchers and practitioners in the field. The authors have strived to produce a text that is pleasant to read, informative, and rigorous - one that reveals both the beautiful nature of the discipline and its practical side.
650			_aMathematical optimization
650			_aOperations research mathematics
650			_aConjugate gradient method
650			_aLagrange multiplier
650			_aLinear programming
650			_aLipschitz continuous
650			_aNewton's method
650			_aNonlinear programming
650			_aQuasi-Newton methods
650			_aWolfe conditions
700			_aWright, Stephen
942			_2ddc _cBK