Simulation Modeling and Analysis, 4th Edition

Title: Simulation Modeling and Analysis, 4th Edition
Author: Averill M. Law
ISBN: 0070667330 / 9780070667334
Format: Soft Cover
Pages: 790
Publisher: TMH
Year: 2011
Availability: Out of Stock
Special Indian Edition

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Simulation Modeling and Analysis provides a comprehensive, state-of-the-art, and technically correct treatment of all important aspects of a simulation study. The book strives to make this material understandable by the use of intuition and numerous figures, examples, and problems. It is equally well suited for use in university courses, simulation practice, and self study.

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  • Latest statistical techniques for estimating the performance measures of a simulated system, both for terminating and steady-state simulations.
  • Comprehensive and practical discussion of how to validate a simulation model.
  • Ranking-and-selection procedures for choosing the best system configuration, which allow the use of common random numbers for increased efficiency.
  • Self-contained discussion of classical design of experiments, with a particular emphasis on how to correctly implement these techniques in the context of simulation modeling.
  • Several detailed examples on the use of simulation-based optimization.

Pedagogy

  • Solved examples: 209
  • Practice problems: 273
  • Latest statistical techniques for estimating the performance measures of a simulated system, both for terminating and steady-state simulations.
  • Self-contained discussion of classical design of experiments, with a particular emphasis on how to correctly implement these techniques in the context of simulation modeling.
  • Several detailed examples on the use of simulation-based optimization.

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List of Symbol
Preface

Chapter 1 : Basic Simulation Modeling
Chapter 2 : Modeling Complex Systems
Chapter 3 : Simulation Software
Chapter 4 : Review of Basic Probability and Statistics
Chapter 5 : Building Valid, Credible, and Appropriately Detailed Simulation Models
Chapter 6 : Selecting Input Probability Distributions
Chapter 7 :
Random-Number Generators
Chapter 8 : Generating Random Variates
Chapter 9 : Output Data Analysis for a Single System
Chapter 10 : Comparing Alternative System Configurations
Chapter 11 : Variance-Reduction Techniques
Chapter 12 :
Experimental Design and Optimization
Chapter 13 :
Simulation of Manufacturing Systems

Appendix
References
Subject Index