Algorithms and Complexity, Giancarlo Bongiovanni; Daniel P. Bovet; Giuseppe D

Название: Network optimization problems : algorithms, applications and complexity
ISBN: 9810212771 ISBN-13(EAN): 9789810212773
Издательство: World Scientific Publishing
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Цена: 16188.00 р. 23126.00 -30%
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Описание: The purpose of this book is to cover a spectrum of developments in network optimization problems, from linear networks to general nonconvex network flow problems.

Автор: Tiziana Calamoneri; Irene Finocchi; Guiseppe F. It
Название: Algorithms and Complexity
ISBN: 354034375X ISBN-13(EAN): 9783540343752
Издательство: Springer
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Цена: 12157.00 р.
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Описание: Covers refereed proceedings of the 6th Italian Conference on Algorithms and Computation, CIAC 2006. This title includes 33 revised full papers together with 3 invited papers which address such topics as sequential, parallel and distributed algorithms, data structures, approximation algorithms, randomized algorithms, and, on-line algorithms.

Автор: Ding-Zhu Du; Ker-I Ko
Название: Advances in Algorithms, Languages, and Complexity
ISBN: 0792343964 ISBN-13(EAN): 9780792343967
Издательство: Springer
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Описание: Contains a collection of sixteen survey papers on developments in algorithms, formal languages, and computational complexity. This title is intended for researchers and graduate students with interests in design and analysis of algorithms, in language theory, and in computational complexity.

Автор: Rosella Petreschi; Giuseppe Persiano; Riccardo Sil
Название: Algorithms and Complexity
ISBN: 3540401768 ISBN-13(EAN): 9783540401766
Издательство: Springer
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Автор: Asmussen
Название: Stochastic Simulation: Algorithms and Analysis
ISBN: 038730679X ISBN-13(EAN): 9780387306797
Издательство: Springer
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Цена: 6981.00 р.
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Описание: Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods , as well as accompanying mathematical analysis of the convergence properties of the methods discussed . The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first  half of the book focusses on general methods, whereas the second half discusses model-specific algorithms. Given the wide range of  examples, exercises and applications students, practitioners and researchers in  probability, statistics, operations research, economics, finance, engineering  as well as biology and chemistry and physics will find the book of value.  Soren Asmussen is Professor of Applied Probability at Aarhus University, Denmark and Peter Glynn is Thomas Ford Professor of  Engineering at Stanford University.