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Mass Transportation Problems: Volume 1: Theory: Probability and Its Applications

Autor Svetlozar T. Rachev, Ludger Rüschendorf
en Limba Engleză Hardback – 24 mar 1998
This is the first comprehensive account of the theory of mass transportation problems and its applications. In volume I, the authors systematically develop the theory of mass transportation with emphasis to the Monge-Kantorovich mass transportation and the Kantorovich-Rubinstein mass transshipment problems, and their various extensions. They discuss a variety of different approaches towards solutions of these problems and exploit the rich interrelations to several mathematical sciences--from functional analysis to probability theory and mathematical economics. The second volume is devoted to applications to the mass transportation and mass transshipment problems to topics in applied probability, theory of moments and distributions with given marginals, queucing theory, risk theory of probability metrics and its applications to various fields, amoung them general limit theorems for Gaussian and non-Gaussian limiting laws, stochastic differential equations, stochastic algorithms and rounding problems. The book will be useful to graduate students and researchers in the fields of theoretical and applied probabilitry, operations research, computer science, and mathematical economics. The prerequisites for this book are graduate level probability theory and real and functional analysis.
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Specificații

ISBN-13: 9780387983509
ISBN-10: 0387983503
Pagini: 508
Ilustrații: XXVI, 508 p.
Dimensiuni: 156 x 234 x 29 mm
Greutate: 0.86 kg
Ediția:1998
Editura: Springer
Colecția Springer
Seria Probability and Its Applications

Locul publicării:New York, NY, United States

Public țintă

Research

Cuprins

The Monge-Kantorovich Problem.- Explicit Results for the Monge-Kantorovich Problem.- Duality Theory for Mass Transfer Problems.- Applications of the Duality Theory.- Mass Transshipment Problems and Ideal Metrics.

Caracteristici

First comprehensive account of the theory of this topic * Authors discuss various approaches and exploit the rich interrelations to several mathematical sciences * Useful to those in theoretical and applied probability, operations research, computer science, and mathematical economics