Models of Network Reliability

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A01=Ilya B. Gertsbakh
A01=Yoseph Shpungin
advanced network reliability algorithms
applied reliability engineering
Author_Ilya B. Gertsbakh
Author_Yoseph Shpungin
BIM
Border States
carlo
Category=KJMV5
Category=PBV
Category=PBW
CDF
CMC
combinatorial optimization
cut
Edge E1
Edge Ej
Edge Failure
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
failure
Failure Probability
francis
group
Importance Measure
Kruskal's Algorithm
Kruskal’s Algorithm
minimal
Minimal Cut Set
Minimal Path Sets
Moment T0
Monotone System
monte
Monte Carlo Algorithm
Mst
Network Lifetime
Network Reliability
Node Reliability
nodes
Parallel Series System
probabilistic risk assessment
probability
Random Variables
Red Process
Reliability Gradient
reliable
Spanning Tree
statistical simulation techniques
stochastic modeling
system failure analysis
Vice Versa

Product details

  • ISBN 9780367384654
  • Weight: 312g
  • Dimensions: 156 x 234mm
  • Publication Date: 05 Sep 2019
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Unique in its approach, Models of Network Reliability: Analysis, Combinatorics, and Monte Carlo provides a brief introduction to Monte Carlo methods along with a concise exposition of reliability theory ideas. From there, the text investigates a collection of principal network reliability models, such as terminal connectivity for networks with unreliable edges and/or nodes, network lifetime distribution in the process of its destruction, network stationary behavior for renewable components, importance measures of network elements, reliability gradient, and network optimal reliability synthesis.

Solutions to most principal network reliability problems—including medium-sized computer networks—are presented in the form of efficient Monte Carlo algorithms and illustrated with numerical examples and tables. Written by reliability experts with significant teaching experience, this reader-friendly text is an excellent resource for software engineering, operations research, industrial engineering, and reliability engineering students, researchers, and engineers.

Stressing intuitive explanations and providing detailed proofs of difficult statements, this self-contained resource includes a wealth of end-of-chapter exercises, numerical examples, tables, and offers a solutions manual—making it ideal for self-study and practical use.

Ilya B. Gertsbakh, Professor Emeritus, Department of Mathematics, Ben Gurion University, Beer Sheva, Israel.

Dr. Gertsbakh has authored more than 70 research papers and six books. He has taught courses in Probability, Statistics, Reliability Theory, and Operations Research. His research interests include Reliability Theory, Probabilistic Methods in Operations Research, and Monte Carlo Methods.

Yoseph Shpungin, Department Head, Software Engineering Department, Shamoon College of Engineering, Beer Sheva, Israel.

Throughout his career, Dr. Shpungin has gained extensive experience in both practical and theoretical operations research and software engineering issues. He has taught courses in Probability, Statistics, Reliability, Algorithms, Databases, and Programming Languages. His field of research is Reliability Theory and Monte Carlo Methods, in which he has authored one book and many publications in international scientific journals and in the proceedings of international conferences.

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