E-Book, Englisch, 375 Seiten
Bandyopadhyay / Bhattacharya Discrete and Continuous Simulation
1. Auflage 2014
ISBN: 978-1-4665-9640-5
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
Theory and Practice
E-Book, Englisch, 375 Seiten
ISBN: 978-1-4665-9640-5
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
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.
Zielgruppe
Academic researchers in industrial/manufacturing/systems engineering, computer sciences, operations research, researchers in transportation, complex systems, operations management, healthcare systems, human-machine systems.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
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
