Numerical Optimization Theoretical and Practical Aspects

Starting with illustrative real-world examples, this book exposes in a tutorial way algorithms for numerical optimization: fundamental ones (Newtonian methods, line-searches, trust-region, sequential quadratic programming, etc.), as well as more specialized and advanced ones (nonsmooth optimization,...

Full description

Bibliographic Details
Main Authors: Bonnans, Joseph-Frédéric, Gilbert, Jean Charles (Author), Lemarechal, Claude (Author), Sagastizábal, Claudia A. (Author)
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2003, 2003
Edition:1st ed. 2003
Series:Universitext
Subjects:
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
LEADER 03791nmm a2200433 u 4500
001 EB000686968
003 EBX01000000000000000540050
005 00000000000000.0
007 cr|||||||||||||||||||||
008 140122 ||| eng
020 |a 9783662050781 
100 1 |a Bonnans, Joseph-Frédéric 
245 0 0 |a Numerical Optimization  |h Elektronische Ressource  |b Theoretical and Practical Aspects  |c by Joseph-Frédéric Bonnans, Jean Charles Gilbert, Claude Lemarechal, Claudia A. Sagastizábal 
250 |a 1st ed. 2003 
260 |a Berlin, Heidelberg  |b Springer Berlin Heidelberg  |c 2003, 2003 
300 |a XIII, 423 p. 7 illus  |b online resource 
505 0 |a 1 General Introduction -- 2 Basic Methods -- 3 Line-Searches -- 4 Newtonian Methods -- 5 Conjugate Gradient -- 6 Special Methods -- 7 Some Theory of Nonsmooth Optimization -- 8 Some Methods in Nonsmooth Optimization -- 9 Bundle Methods. The Quest of Descent -- 10 Decomposition and Duality -- 11 Background -- 12 Local Methods for Problems with Equality Constraints -- 13 Local Methods for Problems with Equality and Inequality Constraints -- 14 Exact Penalization -- 15 Globalization by Line-Search -- 16 Quasi-Newton Versions -- 17 Linearly Constrained Optimization and Simplex Algorithm -- 18 Linear Monotone Complementarity and Associated Vector Fields -- 19 Predictor-Corrector Algorithms -- 20 Non-Feasible Algorithms -- 21 Self-Duality -- 22 One-Step Methods -- 23 Complexity of Linear Optimization Problems with Integer Data -- 24 Karmarkar’s Algorithm -- References 
653 |a Operations Research, Management Science 
653 |a Operations research 
653 |a Optimization 
653 |a Mathematics of Computing 
653 |a Computer science / Mathematics 
653 |a Numerical Analysis 
653 |a Management science 
653 |a Algorithms 
653 |a Calculus of Variations and Optimization 
653 |a Numerical analysis 
653 |a Mathematical optimization 
653 |a Calculus of variations 
700 1 |a Gilbert, Jean Charles  |e [author] 
700 1 |a Lemarechal, Claude  |e [author] 
700 1 |a Sagastizábal, Claudia A.  |e [author] 
041 0 7 |a eng  |2 ISO 639-2 
989 |b SBA  |a Springer Book Archives -2004 
490 0 |a Universitext 
028 5 0 |a 10.1007/978-3-662-05078-1 
856 4 0 |u https://doi.org/10.1007/978-3-662-05078-1?nosfx=y  |x Verlag  |3 Volltext 
082 0 |a 519.6 
520 |a Starting with illustrative real-world examples, this book exposes in a tutorial way algorithms for numerical optimization: fundamental ones (Newtonian methods, line-searches, trust-region, sequential quadratic programming, etc.), as well as more specialized and advanced ones (nonsmooth optimization, decomposition techniques, and interior-point methods). Most of these algorithms are explained in a detailed manner, allowing straightforward implementation. Theoretical aspects are addressed with care, often using minimal assumptions. The present version contains substantial changes with respect to the first edition. Part I on unconstrained optimization has been completed with a section on quadratic programming. Part II on nonsmooth optimization has been thoroughly reorganized and expanded. In addition, nontrivial application problems have been inserted, in the form of computational exercises. These should help the reader to get a better understanding of optimization methods beyond their abstract description, by addressing important features to be taken into account when passing to implementation of any numerical algorithm. This level of detail is intended to familiarize the reader with some of the crucial questions of numerical optimization: how algorithms operate, why they converge, difficulties that may be encountered and their possible remedies.