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Guests | May 15, 2013

Samuel Sattin: IMG Nanny of the Corn

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Fear was my gateway to becoming interested in stories. My nanny growing up, a Scottish expat named Jackie with a fox pelt of red hair and a manic... Continue »
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Discrete-Event Simulation: Modeling, Programming, and Analysis (Springer Series in Operations Research and Financial Enginee)

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Synopses & Reviews

Publisher Comments:

"This is an excellent and well-written text on discrete event simulation with a focus on applications in Operations Research. There is substantial attention to programming, output analysis, pseudo-random number generation and modelling and these sections are quite thorough. Methods are provided for generating pseudo-random numbers (including combining such streams) and for generating random numbers from most standard statistical distributions." --ISI Short Book Reviews, 22:2, August 2002

Synopsis:

Discrete-event simulation consists of a collection of techniques that when applied to a discrete-event dynamical system, generates sequences called sample paths that characterize its behavior. The collection includes modeling concepts for abstracting the essential features of a system, using specially designed software for converting these relationships into computer executable code capable of generating the requisite sample-path data; outlining procedures for converting these data into estimates of systems performances; and then illustrating methods for assessing how well these estimates approximate true, but unknown system behavior. This book is intended for upper level undergraduate and graduate students in operations research and management science, mathematics, industrial engineering, computer science, and business and features extensive exercises throughout.
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Table of Contents

Simulation in Perspective * Modeling Concepts * Data Collection and Averages * Programming and Execution * Search, Space, and Time * Output Analysis * Making Sense of Output and Increasing Efficiency * Sampling from Probability Distributions * Pseudorandom Number Generation * Preparing the Input *

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Product Details

ISBN:
9781441928924
Author:
Fishman, George S.
Publisher:
Springer
Subject:
Number Systems
Subject:
discrete-event simulation
Subject:
simulation modeling
Subject:
Computational Mathematics and Numerical Analysis
Subject:
Simulation and Modeling
Subject:
Economic theory
Subject:
Operations Research/Decision Theory
Subject:
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences This book is designed for upper level undergraduate students and first year graduates taking a first course in simulation. The author takes the approach of carrying common
Subject:
Business Writing
Subject:
Counting & Numeration
Subject:
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
Subject:
Operation Research/Decision Theory
Copyright:
2001
Edition Description:
1st Edition. Softcover version of original hardcover edition 2001
Series:
Springer Series in Operations Research and Financial Engineering
Publication Date:
20110701
Binding:
TRADE PAPER
Language:
English
Pages:
556
Dimensions:
235 x 178 mm
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Related Subjects

Business » Business Plans
Business » General
Business » Management
Business » Strategy
Business » Writing
Computers and Internet » Computers Reference » Computer Simulation
Computers and Internet » Computers Reference » General
Computers and Internet » Personal Computers » General
Science and Mathematics » Mathematics » Basics
Science and Mathematics » Mathematics » Probability and Statistics » General
Science and Mathematics » Mathematics » Probability and Statistics » Statistics

Discrete-Event Simulation: Modeling, Programming, and Analysis (Springer Series in Operations Research and Financial Enginee) New Trade Paper
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Product details 556 pages Springer - English 9781441928924 Reviews:
"Synopsis" by , Discrete-event simulation consists of a collection of techniques that when applied to a discrete-event dynamical system, generates sequences called sample paths that characterize its behavior. The collection includes modeling concepts for abstracting the essential features of a system, using specially designed software for converting these relationships into computer executable code capable of generating the requisite sample-path data; outlining procedures for converting these data into estimates of systems performances; and then illustrating methods for assessing how well these estimates approximate true, but unknown system behavior. This book is intended for upper level undergraduate and graduate students in operations research and management science, mathematics, industrial engineering, computer science, and business and features extensive exercises throughout.
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