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Modern Simulation and Modeling (Wiley Series in Probability and Statistics)
 
 
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Modern Simulation and Modeling (Wiley Series in Probability and Statistics) [Hardcover]

Reuven Y. Rubinstein (Author), Benjamin Melamed (Author)

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Book Description

March 9, 1998 0471170771 978-0471170778 1
A step-by-step guide for today's modeling and simulation practices

This new guide for modeling and simulation of discrete-event systems (DES) demonstrates why simulation is fast becoming the method of choice for the evaluation of system performance in science, engineering, and management. The book begins with the basics of conventional simulation, then proceeds to modern simulation-treating sensitivity analysis and optimization in a wide range of systems that exhibit complex interaction of discrete events. These include communications networks, flexible manufacturing systems, PERT (project evaluation and review techniques) networks, queueing systems, and more.

Less focused on theory than on presenting a clear approach to practical applications, Modern Simulation and Modeling:
* Emphasizes concepts rather than mathematical completeness
* Integrates references and explanations of complex topics into the body of the text
* Provides an innovative chapter on rare-event probability estimation
* Describes the implementation of the score function (SF) method using the NSO simulation package
* Features 40 illustrations and numerous algorithms
* Offers extensive, end-of-chapter exercise sets
* Includes chapter bibliographies for further reading

Modern Simulation and Modeling is an essential text for graduate students of DES and stochastic processes and for undergraduate students in simulation. It is also an excellent reference for professionals in statistics and probability, mathematics, and management science.

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Editorial Reviews

From the Publisher

This book explores modeling and simulation of discrete-event systems (DES), from computer-communication networks, to PERT networks, to flexible manufacturing and queueing systems and more. The book is divided into two parts, one on conventional, the other on modern simulation, with an innovative exploration on rare-event probability estimation. Emphasis is placed on making concepts accessible rather than on mathematical completeness, and each chapter includes extensive exercise sets and a bibliography.

From the Back Cover

A step-by-step guide for today's modeling and simulation practices

This new guide for modeling and simulation of discrete-event systems (DES) demonstrates why simulation is fast becoming the method of choice for the evaluation of system performance in science, engineering, and management. The book begins with the basics of conventional simulation, then proceeds to modern simulation-treating sensitivity analysis and optimization in a wide range of systems that exhibit complex interaction of discrete events. These include communications networks, flexible manufacturing systems, PERT (project evaluation and review techniques) networks, queueing systems, and more.

Less focused on theory than on presenting a clear approach to practical applications, Modern Simulation and Modeling:
* Emphasizes concepts rather than mathematical completeness
* Integrates references and explanations of complex topics into the body of the text
* Provides an innovative chapter on rare-event probability estimation
* Describes the implementation of the score function (SF) method using the NSO simulation package
* Features 40 illustrations and numerous algorithms
* Offers extensive, end-of-chapter exercise sets
* Includes chapter bibliographies for further reading

Modern Simulation and Modeling is an essential text for graduate students of DES and stochastic processes and for undergraduate students in simulation. It is also an excellent reference for professionals in statistics and probability, mathematics, and management science.

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Inside This Book (learn more)
First Sentence:
Monte Carlo simulation (simulation, for short) came to the fore in the first few decades following World War II. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
dominating pdf, highest traffic intensity, score function process, sample performance function, sample performance process, switching regenerative estimators, auxiliary pdf, service time pdf, reference parameter vector, optimal reference vector, regenerative framework, iid variates, interchangeability conditions, sojourn time process, waiting time process, score function method, stochastic counterpart, single simulation run, likelihood ratio process, involving rare events, generating random vectors, bottleneck cut, general queueing networks, original cdf, expected sojourn time
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, New York, Oper Res, Adu Appl, Consider Lindley, Double-Bridge Structure of Figure, Englewood Cliffs, Computer Simul, Performance of Stochastic Counterpart, Boca Raton, Canvas Properties, Fundamentals of Queueing Theory, Marcel Dekker, Master's Thesis, Update Method, West Lafayette
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