Stochastic Programming Problems with Probability and Quantile Functions
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A01=Andrey I. Kibzun
A01=Yuri S. Kan
applications
Author_Andrey I. Kibzun
Author_Yuri S. Kan
Category=PBT
Category=PBWL
communication
concept
definite
electrical
emerged
engineering
entity
eq_isMigrated=1
eq_nobargain
example
fields
force
implicit
increasing
largescale
networks
particularly evident
past
researchers
right
series
structures
study
system
Product details
- ISBN 9780471958154
- Weight: 595g
- Dimensions: 157 x 235mm
- Publication Date: 13 Nov 1995
- Publisher: John Wiley & Sons Inc
- Publication City/Country: US
- Product Form: Hardback
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The concept of a system as an entity in its own right has emerged with increasing force in the past few decades in, for example, the areas of electrical and control engineering, economics, ecology, urban structures, automaton theory, operational research and industry. The more definite concept of a large-scale system is implicit in these applications, but is particularly evident in fields such as the study of communication networks, computer networks and neural networks. The Wiley-Interscience Series in Systems and Optimization has been established to serve the needs of researchers in these rapidly developing fields. It is intended for works concerned with developments in quantitative systems theory, applications of such theory in areas of interest, or associated methodology. Of related interest Stochastic Programming Peter Kall, University of Zurich, Switzerland and Stein W. Wallace, University of Trondheim, Norway Stochastic Programming is the first textbook to provide a thorough and self-contained introduction to the subject. Carefully written to cover all necessary background material from both linear and non-linear programming, as well as probability theory, the book draws together the methods and techniques previously described in disparate sources. After introducing the terms and modelling issues when randomness is introduced in a deterministic mathematical programming model, the authors cover decision trees and dynamic programming, recourse problems, probabilistic constraints, preprocessing and network problems. Exercises are provided at the end of each chapter. Throughout, the emphasis is on the appropriate use of the techniques, rather than on the underlying mathematical proofs and theories, making the book ideal for researchers and students in mathematical programming and operations research who wish to develop their skills in stochastic programming.
Andrey I. Kibzun and Yuri S. Kan are the authors of Stochastic Programming Problems with Probability and Quantile Functions, published by Wiley.
