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El. knyga: Discrete and Continuous Simulation: Theory and Practice

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, (University of Burdwan, WB, India)
  • Formatas: 375 pages
  • Išleidimo metai: 25-Jun-2014
  • Leidėjas: CRC Press Inc
  • Kalba: eng
  • ISBN-13: 9781466596405
Kitos knygos pagal šią temą:
Discrete and Continuous Simulation: Theory and PracticeDidesnis paveikslėlis
  • Formatas: 375 pages
  • Išleidimo metai: 25-Jun-2014
  • Leidėjas: CRC Press Inc
  • Kalba: eng
  • ISBN-13: 9781466596405
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When it comes to discovering glitches inherent in complex systemsbe it a railway or banking, chemical production, medical, manufacturing, or inventory control systemdeveloping 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 humanmachine systems.

Recenzijos

"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

List of Figures xvii
List of Tables xxi
Preface xxiii
Chapter 1 Introduction to Simulation 1(16)
1.1 Introduction
1(1)
1.2 Types of Simulation
2(1)
1.3 Steps of Simulation
3(2)
1.4 Application Areas of Simulation
5(5)
1.4.1 Manufacturing Simulation
5(1)
1.4.2 Transport and Logistics Simulation
6(1)
1.4.3 Military Applications
7(1)
1.4.4 Network Simulation
7(1)
1.4.5 Construction Operations
7(1)
1.4.6 Social Science Applications
8(1)
1.4.7 Environment Applications
8(1)
1.4.8 Health Care Applications
9(1)
1.5 Simulation of Queuing Systems
10(2)
1.6 Simulation of Inventory System
12(2)
1.7 Advantages and Disadvantages of Simulation
14(1)
1.8 Overview of the Remaining
Chapters
14(2)
1.9 Conclusion
16(1)
References
16(1)
Chapter 2 Monte Carlo Simulation 17(16)
2.1 Introduction
17(5)
2.1.1 Examples
17(5)
2.2 Steps of Monte Carlo Simulation
22(1)
2.3 Random Number Generators
23(1)
2.4 Types of Monte Carlo Simulations
24(3)
2.4.1 Crude Monte Carlo
25(1)
2.4.2 Acceptance-Rejection Monte Carlo
26(1)
2.4.3 Stratified Sampling
27(1)
2.4.4 Importance Sampling
27(1)
2.5 Variance Reduction Techniques
27(2)
2.5.1 Common Random Numbers
27(1)
2.5.2 Antithetic Variates
28(1)
2.5.3 Control Variates
29(1)
2.6 When to Use Monte Carlo Simulation
29(1)
2.7 Applications of Monte Carlo Simulation
30(1)
2.8 Advantages and Disadvantages of Monte Carlo Simulation
30(1)
2.8.1 Advantages
30(1)
2.8.2 Disadvantages
31(1)
2.9 Conclusion
31(1)
References
31(2)
Chapter 3 Introduction to Probability Theory 33(20)
3.1 Introduction
33(1)
3.2 Definitions Related to Probability Theory
34(2)
3.3 Brief Introduction to Set Theory
36(7)
3.3.1 Venn Diagram
38(5)
3.4 Counting Techniques
43(1)
3.5 Definition of Probability
44(3)
3.5.1 Classical Definition of Probability
45(1)
3.5.2 Relative Frequency Definition of Probability
45(1)
3.5.3 Axiomatic Definition of Probability
46(1)
3.6 Numerical Examples of Classical Approach to Probability
47(2)
3.7 Laws of Probability
49(2)
3.8 Conclusion
51(1)
References
51(2)
Chapter 4 Probability Distributions 53(26)
4.1 Introduction
53(1)
4.2 Introduction to Random Variables
54(2)
4.3 Discrete and Continuous Probability Distributions
56(5)
4.4 Various Discrete Probability Distributions
61(9)
4.4.1 Discrete Uniform Distribution
63(1)
4.4.2 Binomial Distribution
64(2)
4.4.3 Geometric Distribution
66(1)
4.4.4 Negative Binomial Distribution
67(1)
4.4.5 Hypergeometric Distribution
68(1)
4.4.6 Poisson Distribution
69(1)
4.5 Various Continuous Probability Distributions
70(8)
4.6 Conclusion
78(1)
Reference
78(1)
Chapter 5 Introduction to Random Number Generators 79(26)
5.1 Introduction
79(1)
5.2 Characteristics of a Random Number Generator
79(1)
5.3 Types of Random Number Generators
80(14)
5.3.1 True Random Number Generators
80(2)
5.3.2 Pseudorandom Number Generators
82(8)
5.3.2.1 Linear Congruential Generator
83(3)
5.3.2.2 Multiplicative Congruential Generator
86(1)
5.3.2.3 Inversive Congruential Generator
86(1)
5.3.2.4 Combined LCG
87(1)
5.3.2.5 Lagged Fibonacci Generator
88(1)
5.3.2.6 Mid-Square Method
89(1)
5.3.3 Software Implementation of Pseudorandom Number Generators
90(2)
5.3.3.1 Mersenne Twister Generator
90(1)
5.3.3.2 Marsaglia Generator
91(1)
5.3.4 Attacks on Pseudorandom Number Generators
92(1)
5.3.5 Quasi-Random Number Generators
93(1)
5.4 Tests for Random Number Generators
94(10)
5.4.1 Frequency Test
96(2)
5.4.2 Runs Test
98(1)
5.4.3 Autocorrelation Test
99(1)
5.4.4 Poker Test
100(1)
5.4.5 Gap Test
101(2)
5.4.6 Equidistribution Test
103(1)
5.4.7 Coupon Collectors Test
103(1)
5.4.8 Permutation Test
103(1)
5.4.9 Maximum oft Test
104(1)
5.5 Conclusion
104(1)
Reference
104(1)
Chapter 6 Random Variate Generation 105(24)
6.1 Introduction
105(1)
6.2 Various Methods of Random Variate Generation
106(21)
6.2.1 Linear Search
106(1)
6.2.2 Binary Search
106(1)
6.2.3 Indexed Search
107(1)
6.2.4 Slice Sampling
108(1)
6.2.5 Ziggurat Algorithm
109(1)
6.2.6 MCMC Method
110(1)
6.2.7 Metropolis-Hastings Algorithm
110(1)
6.2.8 Gibbs Sampling
110(1)
6.2.9 Box-Muller Transform Method
111(2)
6.2.9.1 Basic Form
111(1)
6.2.9.2 Polar Form
112(1)
6.2.10 Marsaglia Polar Method
113(1)
6.2.11 Inverse Transform Technique
113(11)
6.2.11.1 Exponential Distribution
114(5)
6.2.11.2 Weibull Distribution
119(2)
6.2.11.3 Uniform Distribution
121(1)
6.2.11.4 Triangular Distribution
122(2)
6.2.12 Convolution Method
124(1)
6.2.12.1 Erlang Distribution
125(1)
6.2.12.2 Binomial Distribution
125(1)
6.2.13 Acceptance-Rejection Method
125(5)
6.2.13.1 Poisson Distribution
126(1)
6.3 Conclusion
127(1)
Reference
127(2)
Chapter 7 Steady-State Behavior of Stochastic Processes 129(24)
7.1 Introduction
129(1)
7.2 Definition of Stochastic Process
130(4)
7.2.1 Classification of Stochastic Processes
131(3)
7.3 Steady-State Conditions in Various Fields
134(1)
7.3.1 Steady-State Condition in Economics
134(1)
7.3.2 Steady-State Condition in Chemistry
134(1)
7.3.3 Steady-State Condition in Electronics
135(1)
7.3.4 Steady-State Condition in Electrical Systems
135(1)
7.4 Various Stochastic Processes
135(15)
7.4.1 Markov Process
136(1)
7.4.2 Poisson Process
136(1)
7.4.3 Gaussian Process
137(1)
7.4.4 Brownian Motion
137(1)
7.4.5 Bernoulli Process
138(1)
7.4.6 Simple Random Walk and Population Processes
139(1)
7.4.7 Stationary Process
139(2)
7.4.8 Autoregressive Process
141(1)
7.4.9 Examples of the Markov Process
142(8)
7.4.10 An Example of the Poisson Process
150(1)
7.5 Conclusion
150(1)
References
151(2)
Chapter 8 Statistical Analysis of Steady-State Parameters 153(6)
8.1 Introduction
153(1)
8.2 Terminating and Steady-State Simulation
154(3)
8.3 Conclusion
157(1)
Reference
157(2)
Chapter 9 Computer Simulation 159(16)
9.1 Introduction
159(1)
9.2 Computer Simulation from Various Aspects
159(1)
9.3 Simulation of Computer Systems
160(11)
9.3.1 Various Components of Computer
160(8)
9.3.1.1 Memory Types
161(2)
9.3.1.2 Monitors or Video Display Unit
163(1)
9.3.1.3 Floppy Disk Drives
163(1)
9.3.1.4 Compact Disk Drives
164(1)
9.3.1.5 Hard Disk Drives
164(1)
9.3.1.6 Overall Method of Execution of Computer Programs
164(1)
9.3.1.7 Software Used in Computers
164(1)
9.3.1.8 Computer Language
165(1)
9.3.1.9 System Software
166(1)
9.3.1.10 Elements of Programming Language
167(1)
9.3.2 Simulation of Various Components of Computer Systems
168(9)
9.3.2.1 Stack
170(1)
9.3.2.2 Queue
171(1)
9.4 Computer Simulations for Various Fields of Study
171(1)
9.5 Game Simulation
172(1)
9.6 Conclusion
173(1)
Reference
173(2)
Chapter 10 Manufacturing Simulation 175(18)
10.1 Introduction
175(1)
10.2 Scheduling
176(1)
10.3 Aspects of Manufacturing for Simulation Study
177(4)
10.3.1 Aspects Considered for Design of Facility Layout
178(1)
10.3.2 Aspects Considered for Design of Material Handling Systems
178(1)
10.3.3 Aspects Considered for Design of Cellular Manufacturing Systems
179(1)
10.3.4 Aspects Considered for Design of FMSs
179(1)
10.3.5 Aspects Considered for Operations Scheduling
179(1)
10.3.6 Aspects Considered for Operating Policies
180(1)
10.3.7 Aspects Considered for Performance Analysis
180(1)
10.4 Selection of Simulation Software
181(1)
10.5 List of Simulation Software Applications
182(9)
10.5.1 Introduction to Arena Simulation Software
182(25)
10.5.1.1 Flowchart Modules
184(5)
10.5.1.2 Data Modules
189(2)
10.6 Conclusion
191(1)
eferences
191(2)
Chapter 11 Manufacturing and Supply Chain Simulation Packages 193(12)
11.1 Introduction
193(1)
11.2 Introduction to C Language
194(3)
11.3 Introduction to C++ Language
197(1)
11.4 Introduction to AweSim Simulation Software
198(2)
11.5 Introduction to Beer Distribution Game Simulation
200(3)
11.6 Conclusion
203(1)
References
203(2)
Chapter 12 Supply Chain Simulation 205(22)
12.1 Introduction
205(2)
12.2 Areas of Supply Chain Simulation
207(13)
12.2.1 Distribution in Supply Chain
208(1)
12.2.2 Collaborative Planning, Forecasting, and Replenishment
208(1)
12.2.3 Supply Chain Performance Measure
209(11)
12.2.3.1 Various Performance Measures and Metrics
211(9)
12.2.4 Methodologies Used in the Existing Literature
220(1)
12.3 Types of Supply Chain Simulations
220(2)
12.4 Types of Supply Chain Simulation Software
222(1)
12.5 Conclusion
223(1)
References
223(4)
Chapter 13 Simulation in Various Disciplines 227(14)
13.1 Introduction
227(1)
13.2 Simulation in Electronics Engineering
227(2)
13.2.1 Open Access Software
228(1)
13.2.2 Proprietary Software
228(1)
13.3 Simulation in Chemical Engineering
229(1)
13.4 Simulation in Aerospace Engineering
230(1)
13.5 Simulation in Civil Engineering
231(1)
13.6 Simulation in Other Disciplines
232(3)
13.7 Some Selected Simulation Packages
235(4)
13.7.1 FLUENT
235(1)
13.7.2 TRNSYS
236(1)
13.7.3 EASY5
237(1)
13.7.4 GENESIS
237(1)
13.7.5 BetaSim
237(1)
13.7.6 AMESim
238(1)
13.7.7 SimOne
238(1)
13.7.8 LogiSim
238(1)
13.7.9 DWSIM
239(1)
13.8 Conclusion
239(1)
References
239(2)
Chapter 14 Simulation of Complex Systems 241(8)
14.1 Introduction
241(1)
14.2 Advantages and Disadvantages of Simple Systems
242(1)
14.3 Effective Tools to Simulate and Analyze Complex Systems
243(4)
14.4 Conclusion
247(1)
References
247(2)
Chapter 15 Simulation with Cellular Automata 249(6)
15.1 Introduction
249(1)
15.2 Cellular Automata
249(2)
15.3 Types of Simulation with Cellular Automata
251(1)
15.4 Applications of Cellular Automata
251(1)
15.5 Software for Cellular Automata
252(1)
15.6 Conclusion
252(1)
References
253(2)
Chapter 16 Agent-Based Simulation 255(22)
16.1 Background
255(1)
16.2 Characteristics of Agents
255(2)
16.3 Types of Agents
257(2)
16.4 Phases of General Agent-Based Simulation
259(1)
16.5 Design of Agents
260(2)
16.6 Multiagent-Based Simulation in Manufacturing
262(2)
16.7 Some Multiagent Models
264(8)
16.7.1 Gaia Methodology
264(1)
16.7.2 ROADMAP Methodology
265(1)
16.7.3 Prometheus Methodology
266(1)
16.7.4 PASSI Methodology
267(2)
16.7.5 MaSE Methodology
269(2)
16.7.6 Tropos Methodology
271(1)
16.8 Applications of Agent-Based Simulation
272(1)
16.9 Conclusion
273(1)
References
273(4)
Chapter 17 Continuous System Simulation 277(18)
17.1 Introduction
277(1)
17.2 Approaches to Continuous System Simulation
277(2)
17.2.1 Ordinary Differential Equations
277(1)
17.2.2 Partial Differential Equations
278(1)
17.3 Integration Methods
279(4)
17.3.1 Euler Method
280(1)
17.3.2 Predictor-Corrector Method
281(1)
17.3.3 Runge-Kutta Method
282(1)
17.4 Validation Schemes
283(3)
17.4.1 External Validation Based on Qualitative Comparisons of Dynamic Response Data
284(1)
17.4.2 External Validation Based on System Identification Techniques
285(1)
17.4.3 Category Based on Parameter Sensitivity
286(1)
17.5 Application Areas of Continuous System Simulation
286(1)
17.6 Evolution of CSSLs
286(1)
17.7 Features of CSSLs
287(1)
17.8 Types of CSSLs
288(1)
17.9 Introduction to Some CSSLs
288(4)
17.9.1 Languages for Ordinary Differential Equations
288(2)
17.9.1.1 MIMIC
289(1)
17.9.1.2 DYNAMO
289(1)
17.9.1.3 CSMP-III
289(1)
17.9.1.4 SL-1
290(1)
17.9.1.5 PROSE
290(1)
17.9.1.6 SLANG
290(1)
17.9.2 Languages for Partial Differential Equations
290(11)
17.9.2.1 SALEM
291(1)
17.9.2.2 PDEL
291(1)
17.9.2.3 LEANS
291(1)
17.9.2.4 DSS
292(1)
17.9.2.5 PDELAN
292(1)
17.10 Conclusion
292(1)
References
292(3)
Chapter 18 Introduction to Simulation Optimization 295(6)
18.1 Introduction
295(1)
18.2 Aspects of Optimization for Simulation
296(1)
18.3 Major Issues and Advantages of Simulation Optimization
297(1)
18.4 Commercial Packages for Simulation Optimization
297(1)
18.5 Application Areas of Simulation Optimization
298(1)
18.6 Conclusion
298(1)
References
299(2)
Chapter 19 Algorithms for Simulation Optimization 301(10)
19.1 Introduction
301(1)
19.2 Major Techniques
301(7)
19.2.1 Gradient-Based Search Techniques
302(3)
19.2.1.1 Finite Difference Estimation
304(1)
19.2.1.2 LR Estimators
304(1)
19.2.1.3 Perturbation Analysis
304(1)
19.2.1.4 Frequency Domain Experiments
305(1)
19.2.2 Stochastic Optimization
305(1)
19.2.3 Response Surface Methodology
305(1)
19.2.4 Heuristic Methods
306(2)
19.2.4.1 Genetic Algorithm
306(1)
19.2.4.2 Evolutionary Strategy
306(1)
19.2.4.3 Simulated Annealing
307(1)
19.2.4.4 Tabu Search
307(1)
19.2.4.5 Simplex Search
308(1)
19.2.4.6 A-Teams
308(1)
19.2.4.7 Sampling Method
308(1)
19.3 Some Other Techniques
308(2)
19.3.1 DIRECT Optimization Algorithm
308(1)
19.3.2 UOBYQA Optimization Algorithm
309(1)
19.3.3 Splash
309(1)
19.4 Conclusion
310(1)
References
310(1)
Chapter 20 Simulation with System Dynamics 311(12)
20.1 Introduction
311(1)
20.2 Important Concepts Related to System Dynamics
311(3)
20.2.1 Feedback Loop
311(1)
20.2.2 Positive and Negative Feedback
312(1)
20.2.3 First-Order Negative Feedback Loop
313(1)
20.2.4 Second-Order Negative Feedback Loop
314(1)
20.3 Steps in Modeling with System Dynamics
314(2)
20.4 System Dynamics Tools
316(4)
20.4.1 Causal Loop Diagrams
317(1)
20.4.2 Stock and Flow Maps
318(1)
20.4.3 Model Boundary Chart
319(1)
20.5 System Dynamics Software
320(1)
20.6 Conclusion
320(1)
References
321(2)
Chapter 21 Simulation Software 323(12)
21.1 Introduction
323(1)
21.2 Types of Studies on Simulation Software
324(2)
21.3 Various Methods of Selecting Simulation Software
326(4)
21.4 Simulation Software Evaluation
330(4)
21.4.1 Model Input
331(1)
21.4.2 Model Execution
332(1)
21.4.3 Animation Facilities
332(1)
21.4.4 Testing and Debugging
333(1)
21.4.5 Output of the Simulation Experiment
333(1)
21.5 Conclusion
334(1)
References
334(1)
Chapter 22 Future Trends in Simulation 335(10)
22.1 Introduction
335(1)
22.2 .NET Technologies
336(4)
22.2.1 C# .NET
338(2)
22.3 Cloud Virtualization
340(4)
22.4 Conclusion
344(1)
References
344(1)
Index 345
Susmita Bandyopadhyay, Ranjan Bhattacharya
Daugiau apie elektronines knygas Daugiau apie elektronines knygas
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