Discrete and Continuous Simulation: Theory and Practice, 1st Edition (Paperback) book cover

Discrete and Continuous Simulation

Theory and Practice, 1st Edition

By Susmita Bandyopadhyay, Ranjan Bhattacharya

CRC Press

375 pages | 106 B/W Illus.

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Description

When it comes to discovering glitches inherent in complex systems—be it a railway or banking, chemical production, medical, manufacturing, or inventory control system—developing a simulation of a system can identify problems with less time, effort, and disruption than it would take to employ the original. Advantageous to both academic and industrial practitioners, Discrete and Continuous Simulation: Theory and Practice offers a detailed view of simulation that is useful in several fields of study.

This text concentrates on the simulation of complex systems, covering the basics in detail and exploring the diverse aspects, including continuous event simulation and optimization with simulation. It explores the connections between discrete and continuous simulation, and applies a specific focus to simulation in the supply chain and manufacturing field. It discusses the Monte Carlo simulation, which is the basic and traditional form of simulation. It addresses future trends and technologies for simulation, with particular emphasis given to .NET technologies and cloud computing, and proposes various simulation optimization algorithms from existing literature.

  • Includes chapters on input modeling and hybrid simulation
  • Introduces general probability theory
  • Contains a chapter on Microsoft® Excel and MATLAB®/Simulink®
  • Discusses various probability distributions required for simulation
  • Describes essential random number generators

Discrete and Continuous Simulation: Theory and Practice defines the simulation of complex systems. This text benefits academic researchers in industrial/manufacturing/systems engineering, computer sciences, operations research, and researchers in transportation, operations management, healthcare systems, and human–machine systems.

Reviews

"…presents topics of practical importance for both using and building simulation models, and introduces these in a way that emphasizes how each new concept is applied in practice. The book also offers a unique overview of how broadly simulation is applied in industry and for research…"

––James Nutaro, Oak Ridge National Laboratory, Tennessee, USA

"The book provides a comprehensive, elaborate, extensive account of computer simulation, of discrete and continuous simulation with basic probability theory, stochastic processes with application to manufacturing, supply chains, cellular automata and agent-based simulation, and systems simulation and optimization.The also book provides a detailed description of simulation software and languages with application to cloud computing, discussion of NET technologies and many software tools. The authors mention several disciples in engineering. There are many figures and tables to explain the process of simulation."

Nirode C. Mohanty, Zentralblatt MATH (zbMATH), Germany

Table of Contents

Introduction to Simulation

Introduction

Types of Simulation

Steps of Simulation

Application Areas of Simulation

Simulation of Queuing Systems

Simulation of Inventory System

Advantages and Disadvantages of Simulation

Overview of the Remaining s

Conclusion

References

Monte Carlo Simulation

Introduction

Examples

Steps of Monte Carlo Simulation

Random Number Generators

Types of Monte Carlo Simulation

Crude Monte Carlo

Acceptance–Rejection Monte Carlo

Stratified Sampling

Importance Sampling

Variance Reduction Techniques

Common Random Numbers

Antithetic Variates

Control Variates

When to Use Monte Carlo Simulation

Applications of Monte Carlo Simulation

Advantages and Disadvantages of Monte Carlo Simulation

Conclusion

References

Introduction to Probability Theory

Introduction

Definitions Related to Probability Theory

Brief Introduction to Set Theory

Counting Techniques

Definition of Probability

Numerical Examples on Classical Approach to Probability

Laws of Probability

Conclusion

References

Probability Distributions

Introduction

Introduction to Random Variables

Discrete and Continuous Probability Distributions

Various Discrete Probability Distributions

Various Continuous Probability Distributions

Conclusion

Reference

Introduction to Random Number Generators

Introduction

Characteristics of a Random Number Generator

Types of Random Number Generators

Tests for Random Number Generators

Conclusion

Reference

Random Variate Generation

Introduction

Various Methods of Random Variate Generation

Conclusion

Steady-State Behavior of Stochastic Processes

Introduction

Definition of Stochastic Process

Steady-State Conditions in Various Fields

Various Stochastic Processes

Conclusion

References

Statistical Analysis of Steady-State Parameters

Introduction

Terminating and Steady-State Simulation

Conclusion

Reference

Computer Simulation

Introduction

Computer Simulation from Various Aspects

Simulation of Computer Systems

Computer Simulation for Various Fields of Study

Game Simulation

Conclusion

Reference

Manufacturing Simulation

Introduction

Scheduling

Aspects of Manufacturing for Simulation Study

Selection of Simulation Software

List of Simulation Software

Conclusion

References

Manufacturing and Supply Chain Simulation Packages

Introduction

Introduction to C Language

Introduction to C++ Language

Introduction to AweSim Simulation Software

Introduction to Beer Distribution Game Simulation

Conclusion

References

Supply Chain Simulation

Introduction

Areas of Supply Chain Simulation

Types of Supply Chain Simulation

Types of Supply Chain Simulation Software

Conclusion

References

Simulation in Various Disciplines

Introduction

Simulation in Electronics Engineering

Simulation in Chemical Engineering

Simulation in Aerospace Engineering

Simulation in Civil Engineering

Simulation in Other Disciplines

Some Selected Simulation Packages

Conclusion

References

Simulation of Complex Systems

Introduction

Advantages and Disadvantages of Simple Systems

Effective Tools to Simulate and Analyze Complex Systems

Conclusion

References

Simulation with Cellular Automata

Introduction

Cellular Automata

Simulation with Cellular Automata

Applications of Cellular Automata

Software for Cellular Automata

Conclusion

References

Agent-Based Simulation

Background

Characteristics of the Agents

Types of Agents

Phases of General Agent-Based Simulation

Design of Agents

Multiagent-Based Simulation in Manufacturing

Some Multiagent Models

Applications of Agent-Based Simulation

Conclusion

References

Continuous System Simulation

Introduction

Approaches to Continuous System Simulation

Integration Methods

Validation Schemes

Application Areas of Continuous System Simulation

Evolution of CSSLs

Features of CSSLs

Types of CSSLs

Introduction to Some CSSLs

Conclusion

References

Introduction to Simulation Optimization

Introduction

Aspects of Optimization for Simulation

Major Issues and Advantages of Simulation Optimization

Commercial Packages for Simulation Optimization

Application Areas of Simulation Optimization

Conclusion

References

Algorithms for Simulation Optimization

Introduction

Major Techniques

Some Other Techniques

Conclusion

References

Simulation with System Dynamics

Introduction

Important Concepts Related to System Dynamics

Steps of Modeling with System Dynamics

System Dynamics Tools

System Dynamics Software

Conclusion

References

Simulation Software

Introduction

Types of Studies on Simulation Software

Various Methods of Selecting Simulation Software

Software Evaluation

Conclusion

References

Future Trends of Simulation

Introduction

NET Technologies

Cloud Virtualization

Conclusion

References

Index

Subject Categories

BISAC Subject Codes/Headings:
MAT000000
MATHEMATICS / General
TEC009000
TECHNOLOGY & ENGINEERING / Engineering (General)
TEC029000
TECHNOLOGY & ENGINEERING / Operations Research