Modified lagrangians and monotone maps in optimization

This translation of the important Russian text covers the theory and computational methods of modified Lagrangian functions (MLFs)--a new branch of mathematical programming used to solve optimization problems. Providing a thorough analysis for both traditional convex programming and monotone maps, t...

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Bibliographic Details
Main Author: Gol'shteĭn, E. G. (Evgeniĭ Grigor'evich)
Other Authors: Tret'i'a'kov, N. V. (Nikolaĭ Vladimirovich)
Format: Book
Language:English
Published: New York John Wiley & Sons 1996
Series:Wiley-Interscience series in discrete mathematics and optimization
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020 |a 0471548219 (cloth : acid-free paper) 
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040 |a UPNM 
090 |a QA 402.5  |b .G6513 1996 
100 1 |a Gol'shteĭn, E. G.  |q (Evgeniĭ Grigor'evich). 
240 1 0 |a Modifit's'irovannye funkt's'ii Lagranzha.  |l English 
245 1 0 |a Modified lagrangians and monotone maps in optimization  |c E.G. Golshtein and N.V. Tretyakov ; translated by N.V. Tretyakov. 
260 |a New York  |b John Wiley & Sons  |c 1996 
300 |a ix, 438 p.  |c 24cm. 
490 1 |a Wiley-Interscience series in discrete mathematics and optimization 
500 |a "A Wiley-Interscience publication." 
504 |a Includes bibliographical reference and index 
505 |a 1. Introduction to Convex Analysis -- 2. Modified Lagrangian Functions for Convex Programming Problems -- 3. Dual Methods -- 4. Monotone Maps -- 5. Gradient-Type Methods and Modification of a Monotone Map -- 6. Saddle Gradient Methods -- 7. Modified Lagrangian Functions For Smooth Mathematical Programming Problems And Related Dual Methods. 
520 |a This translation of the important Russian text covers the theory and computational methods of modified Lagrangian functions (MLFs)--a new branch of mathematical programming used to solve optimization problems. Providing a thorough analysis for both traditional convex programming and monotone maps, the book shows the advantages of MLFs over classical Lagrangian functions in such practical applications as numerical algorithms, economic modeling, de-composition, and nonconvex local constrained optimization. Following an overview of convex analysis, the authors introduce MLFs through the more general formalism of weak modified Lagrangian functions (WMLFs). They use the two concepts to develop a theory of duality supported by examples of elementary economic models. Also examined are the benefits of MLFs in the application of dual methods in linear programming and in problems with inconsistent constraints. 
650 0 |a Mathematical optimization 
650 0 |a Lagrangian functions 
700 1 |a Tret'i'a'kov, N. V.  |q (Nikolaĭ Vladimirovich) 
830 0 |a Wiley-Interscience series in discrete mathematics and optimization 
999 |a vtls000002849  |c 2919  |d 2919