Linear Optimization Problems with Inexact Data

Linear Optimization Problems with Inexact Data

AngličtinaPevná vazba
Fiedler Miroslav
Springer-Verlag New York Inc.
EAN: 9780387326979
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Podrobné informace

Linear programming attracted the interest of mathematicians during and after World War II when the first computers were constructed and methods for solving large linear programming problems were sought in connection with specific practical problems—for example, providing logistical support for the U.S. Armed Forces or modeling national economies. Early attempts to apply linear programming methods to solve practical problems failed to satisfy expectations. There were various reasons for the failure. One of them, which is the central topic of this book, was the inexactness of the data used to create the models. This phenomenon, inherent in most pratical problems, has been dealt with in several ways. At first, linear programming models used "average" values of inherently vague coefficients, but the optimal solutions of these models were not always optimal for the original problem itself. Later researchers developed the stochastic linear programming approach, but this too has its limitations. Recently, interest has been given to linear programming problems with data given as intervals, convex sets and/or fuzzy sets. The individual results of these studies have been promising, but the literature has not presented a unified theory. Linear Optimization Problems with Inexact Data attempts to present a comprehensive treatment of linear optimization with inexact data, summarizing existing results and presenting new ones within a unifying framework.

EAN 9780387326979
ISBN 0387326979
Typ produktu Pevná vazba
Vydavatel Springer-Verlag New York Inc.
Datum vydání 20. dubna 2006
Stránky 214
Jazyk English
Rozměry 235 x 155
Země United States
Sekce Professional & Scholarly
Autoři Fiedler Miroslav; Nedoma Josef; Ramik Jaroslav; Rohn Jiri; Zimmermann Karel
Ilustrace XVI, 214 p. 5 illus.
Edice 2006 ed.
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