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Item #:
89898597
Wiley Interscience Systems and Optimizat Stochastic Programming Problems, Book 9, (Hardcover)
Item #:
89898597
KES 47166
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This book is the first textbook to provide a thorough and self-contained introduction to Stochastic Programming, drawing together techniques previously described in disparate sources.
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What Stands Out
Comprehensive Coverage
This book provides in-depth analysis of stochastic programming, integrating probability and quantile functions for comprehensive understanding, appealing to both researchers and students in optimization fields.
Practical Applications
Offers real-world applications and solving strategies, bridging theoretical concepts with practical scenarios, making it invaluable for professionals needing effective solutions to complex optimization problems.
Expert Insights
Authored by leading experts, it delivers high-quality content and advanced methodologies, ensuring readers gain valuable knowledge from authoritative sources in the field of stochastic programming.
Product Details
- 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.
| Book format | Hardcover |
| Fiction/nonfiction | Non-Fiction |
| Genre | Textbooks |
| Publication date | August, 1996 |
| Pages | 315 |
| Subgenre | Linear & Nonlinear Programming |
| Series title | Wiley Interscience Systems and Optimization |
| Number in series | 9 |
| Edition | 1 |
| Publisher | John Wiley and Sons, Inc. |
| Original languages | English |
| Language | English |
| Edu focus | Mathematics |
| Is collectible | N |
| Binding type | Case Binding |
| Recording time | 0 min |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 6.34 x 0.94 x 9.32 in (16.1 x 2.4 x 23.7 cm) |
| Assembled product weight | 1.34 lb (610 grams) |
| Bisac subject heading | Mathematics |
Who Should Buy?
-
Graduate Students
Ideal for advanced students in operations research, providing theoretical insights and practical applications in stochastic programming.
-
Researchers
Beneficial for researchers focusing on optimization and probability, offering detailed methodologies and case studies in stochastic settings.
-
Professionals
Useful for industry professionals dealing with uncertainty in data, assisting in decision-making under probabilistic models.
-
Beginner Students
Not suitable for beginners lacking foundational knowledge in programming or optimization, as it delves into advanced topics.
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Features & Benefits
- First comprehensive introduction to Stochastic Programming.
- Covers both linear and non-linear programming essentials.
- Includes decision trees, dynamic programming, and probabilistic constraints.
- Focuses on practical application of techniques over mathematical proofs.
- Ideal for researchers and students in mathematical programming.
- Exercises provided at the end of each chapter to reinforce learning.
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