Linear and Nonlinear Programming

"Linear and Nonlinear Programming" is considered a classic textbook in Optimization. While it is a classic, it also reflects modern theoretical insights. These insights provide structure to what might otherwise be simply a collection of techniques and results, and this is valuable both as...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Luenberger, David G. (Συγγραφέας), Ye, Yinyu (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Boston, MA : Springer US, 2008.
Έκδοση:Third Edition.
Σειρά:International Series in Operations Research & Management Science, 116
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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505 0 |a Linear Programming -- Basic Properties of Linear Programs -- The Simplex Method -- Duality -- Interior-Point Methods -- Transportation and Network Flow Problems -- Unconstrained Problems -- Basic Properties of Solutions and Algorithms -- Basic Descent Methods -- Conjugate Direction Methods -- Quasi-Newton Methods -- Constrained Minimization -- Constrained Minimization Conditions -- Primal Methods -- Penalty and Barrier Methods -- Dual and Cutting Plane Methods -- Primal-Dual Methods. 
520 |a "Linear and Nonlinear Programming" is considered a classic textbook in Optimization. While it is a classic, it also reflects modern theoretical insights. These insights provide structure to what might otherwise be simply a collection of techniques and results, and this is valuable both as a means for learning existing material and for developing new results. One major insight of this type is the connection between the purely analytical character of an optimization problem, expressed perhaps by properties of the necessary conditions, and the behavior of algorithms used to solve a problem. This was a major theme of the first and second editions. Now the third edition has been completely updated with recent Optimization Methods. Yinyu Ye has written chapters and chapter material on a number of these areas including Interior Point Methods. This book is designed for either self-study by professionals or classroom work at the undergraduate or graduate level for technical students. Like the field of optimization itself, which involves many classical disciplines, the book should be useful to system analysts, operations researchers, numerical analysts, management scientists, and other specialists. . 
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