Simulation modeling and analysis:
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| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Boston [u.a.]
McGraw Hill Education
2015
|
| Edition: | 5. ed. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XVIII, 776, [4] S. Ill., graph. Darst. |
| ISBN: | 9780073401324 |
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MARC
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| 100 | 1 | |a Law, Averill M. |e Verfasser |0 (DE-588)170238075 |4 aut | |
| 245 | 1 | 0 | |a Simulation modeling and analysis |c Averill M. Law |
| 250 | |a 5. ed. | ||
| 264 | 1 | |a Boston [u.a.] |b McGraw Hill Education |c 2015 | |
| 300 | |a XVIII, 776, [4] S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 650 | 4 | |a Digital computer simulation | |
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| 999 | |a oai:aleph.bib-bvb.de:BVB01-027219750 | ||
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| _version_ | 1804152084032913408 |
|---|---|
| adam_text | CONTENTS
.ι^|Jl:ίll|ï lL^lιH!!№ιlllMMlWШťli!W№ l^ιll)IWlίl^lllfflM^WI^ľiίWГl!1¡^ґ^Tι , , fV 1
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List of Symbols
xiii
Preface
xvi
Chapter
1
Basic Simulation Modeling
1
1.1
The Nature of Simulation
1
1.2
Systems, Models, and Simulation
3
1.3
Discrete-Event Simulation
6
1.3.1
Time-Advance Mechanisms
7
1.3.2
Components and Organization of a Discrete-Event
Simulation Model
9
1.4
Simulation of a Single-Server Queueing System
12
1.4.1
Problem Statement
12
1.4.2
Intuitive Explanation
18
1.4.3
Program Organization and Logic
27
1.4.4
С
Program
32
1.4.5
Simulation Output and Discussion
39
1.4.6
Alternative Stopping Rules
41
1.4.7
Determining the Events and Variables
45
1.5
Simulation of an Inventory System
48
1.5.1
Problem Statement
48
1.5.2
Program Organization and Logic
50
1.5.3
С
Program
53
1.5.4
Simulation Output and Discussion
60
1.6
Parallel/Distributed Simulation and the High Level Architecture
61
1.6.1
Parallel Simulation
62
1.6.2
Distributed Simulation and the High Level Architecture
64
.,7
Steps in a Sound Simulation Study
66
1.8
Advantages, Disadvantages, and Pitfalls of Simulation
70
Appendix 1A: Fixed-Increment Time Advance
72
Appendix IB: A Primer on Queueing Systems
73
1
B.
1
Components of a Queueing System
74
IB.
2
Notation for Queueing Systems
74
1B.3 Measures of Performance for Queueing Systems
75
Problems
78
VI
CONTENTS
Chapter
2
Modeling Complex Systems
85
2.1
Introduction
85
2.2
List Processing in Simulation
86
2.2.1
Approaches to Storing Lists in
a Computer
86
2.2.2
Linked Storage Allocation
87
2.3
A Simple Simulation Language: simlib
93
2.4
Single-Server Queueing Simulation with simlib
102
2.4.1
Problem Statement
102
2.4.2
simlib Program
102
2.4.3
Simulation Output and Discussion
107
2.5
Time-Shared Computer Model
108
2.5.1
Problem Statement
108
2.5.2
simlib Program
109
2.5.3
Simulation Output and Discussion
117
2.6
Multiteller Bank with Jockeying
120
2.6.1
Problem Statement
120
2.6.2
simlib Program
121
2.6.3
Simulation Output and Discussion
131
2.7
Job-Shop Model
134
2.7.1
Problem Statement
134
2.7.2
simlib Program
136
2.7.3
Simulation Output and Discussion
147
2.8
Efficient Event-List Management
149
Appendix
2
А: С
Code for simlib
150
Problems
163
Chapter
3
Simulation Software
181
3.1
Introduction
181
3.2
Comparison of Simulation Packages with
Programming Languages
182
3.3
Classification of Simulation Software
183
3.3.1
General-Purpose vs. Application-Oriented
Simulation Packages
183
3.3.2
Modeling Approaches
183
3.3.3
Common Modeling Elements
186
3.4
Desirable Software Features
186
3.4.1
General Capabilities
187
3.4.2
Hardware and Software Requirements
189
3.4.3
Animation and Dynamic Graphics
189
3.4.4
Statistical Capabilities
190
3.4.5
Customer Support and Documentation
192
3.4.6
Output Reports and Graphics
193
CONTENTS
VII
3.5 General-Purpose Simulation
Packages
193
3.5.1
Arena ^
193
3.5.2
ExtendSim
198
3.5.3
Simio
206
3.5.4
Other
Genera]
-Purpose Simulation Packages
212
3.6
Object-Oriented Simulation
212
3.7
Examples of Application-Oriented Simulation Packages
213
Chapter
4
Review of Basic Probability and Statistics
214
4.1
Introduction
214
4.2
Random Variables and Their Properties
214
4.3
Simulation Output Data and Stochastic Processes
226
4.4
Estimation of Means, Variances, and Correlations
229
4.5
Confidence Intervals and Hypothesis Tests for the Mean
233
4.6
The Strong Law of Large Numbers
240
4.7
The Danger of Replacing a Probability Distribution by
its Mean
241
Appendix 4A: Comments on Covariance-Stationary Processes
241
Problems
242
Chapter
5
Building Valid, Credible, and Appropriately Detailed
Simulation Models
246
5.1
Introduction and Definitions
246
5.2
Guidelines for Determining the Level of Model Detail
249
5.3
Verification of Simulation Computer Programs
251
5.4
Techniques for Increasing Model Validity and Credibility
255
5.4.1
Collect High-Quality Information and
Data on the System
256
5.4.2
Interact with the Manager on a Regular Basis
257
5.4.3
Maintain a Written Assumptions Document
and Perform a Structured Walk-Through
258
5.4.4
Validate Components of the Model by
Using Quantitative Techniques
260
5.4.5
Validate the Output from the Overall Simulation Model
262
5.4.6
Animation
268
5.5
Management s Role in the Simulation Process
269
5.6
Statistical Procedures for Comparing Real-World
Observations and Simulation Output Data
269
5.6.1
Inspection Approach
270
5.6.2
Confidence-Interval Approach Based on
Independent Data
273
5.6.3
Time-Series Approaches
276
5.6.4
Other Approaches
277
Problems
277
Vlil
CONTENTS
Chapter
6
Selecting Input Probability Distributions
279
6.1
Introduction
279
6.2
Useful Probability Distributions
285
6.2.1
Parameterization of Continuous Distributions
285
6.2.2
Continuous Distributions
286
6.2.3
Discrete Distributions
305
6.2.4
Empirical Distributions
305
6.3
Techniques for Assessing Sample Independence
316
6.4
Activity I: Hypothesizing Families of Distributions
319
6.4.1
Summary Statistics
320
6.4.2
Histograms
322
6.4.3
Quantile Summaries and Box Plots
324
6.5
Activity II: Estimation of Parameters
330
6.6
Activity III: Determining How Representative
the Fitted Distributions Are
334
6.6.1
Heuristic Procedures
335
6.6.2
Goodness-of-Fit Tests
344
6.7
The ExpertFit Software and an Extended Example
359
6.8
Shifted and Truncated Distributions
364
6.9
Bézier
Distributions
366
6.10
Specifying Multivariate Distributions, Correlations,
and Stochastic Processes
367
6.10.1
Specifying Multivariate Distributions
368
6.10.2
Specifying Arbitrary Marginal Distributions
and Correlations
372
6.10.3
Specifying Stochastic Processes
373
6.11
Selecting a Distribution in the Absence of Data
375
6.12
Models of Arrival Processes
380
6.12.1
Poisson
Processes
380
6.12.2
Nonstationary
Poisson
Processes
381
6.12.3
Batch Arrivals
384
6.13
Assessing the Homogeneity of Different Data Sets
385
Appendix 6A: Tables of MLEs for the Gamma and
Beta Distributions
386
Problems
389
Chapter
7
Random-Number Generators
393
7.1
Introduction
393
7.2
Linear Congruential Generators
397
7.2.1
Mixed Generators
399
7.2.2
Multiplicative Generators
400
7.3
Other Kinds of Generators
402
7.3.1
More General Congruences
402
CONTENTS
IX
7.3.2
Composite
Generators 403
7.3.3
Feedback
Shift
Register Generators 405
7.4
Testing Random-Number
Generators 409
7.4.1
Empirical
Tests 409
7.4.2
Theoretical
Tests 414
7.4.3
Some
General
Observations on Testing
418
Appendix
7
A: Portable
С
Code for a PMMLCG
419
Appendix 7B
:
Portable
С
Code for a Combined MRG
421
Problems
423
Chapter
8
Generating Random
Variâtes
426
8.1
Introduction
426
8.2
General Approaches to Generating Random
Variâtes
428
8.2.1
Inverse Transform
428
8.2.2
Composition
437
8.2.3
Convolution
440
8.2.4
Acceptance-Rejection
441
8.2.5
Ratio of Uniforms
448
8.2.6
Special Properties
450
8.3
Generating Continuous Random
Variâtes
451
8.3.1
Uniform
452
8.3.2
Exponential
452
8.3.3
m-Erlang
453
8.3.4
Gamma
453
8.3.5
Weibull
456
8.3.6
Normal
457
8.3.7 Lognormal 458
8.3.8
Beta
458
8.3.9
Pearson Type V
459
8.3.10
Pearson Type VI
460
8.3.11
Log-Logistic
460
8.3.12
Johnson Bounded
460
8.3.13
Johnson Unbounded
461
8.3.14
Bézier
461
8.3.15
Triangular
461
8.3.16
Empirical Distributions
462
8.4
Generating Discrete Random
Variâtes
463
8.4.1
Bernoulli
464
8.4.2
Discrete Uniform
464
8.4.3
Arbitrary Discrete Distribution
464
8.4.4
Binomial
469
8.4.5
Geometric
469
8.4.6
Negative Binomial
469
8.4.7
Poisson
470
X
CONTENTS
8.5
Generating Random Vectors, Correlated Random
Variâtes,
and Stochastic Processes
470
8.5.1
Using Conditional Distributions
471
8.5.2
Multivariate Normal and Multivariate
Lognormal 472
8.5.3
Correlated Gamma Random
Variâtes
473
8.5.4
Generating from Multivariate Families
474
8.5.5
Generating Random Vectors with Arbitrarily
Specified Marginal Distributions and Correlations
474
8.5.6
Generating Stochastic Processes
475
8.6
Generating Arrival Processes
476
8.6.1
Poisson
Processes
476
8.6.2
Nonstationary
Poisson
Processes
477
8.6.3
Batch Arrivals
481
Appendix 8A: Validity of the Acceptance-Rejection
Method
481
Appendix 8B: Setup for the Alias Method
482
Problems
483
Chapter
9
Output Data Analysis for a Single System
488
9.1
Introduction
488
9.2
Transient and Steady-State Behavior of a Stochastic Process
491
9.3
Types of Simulations with Regard to Output Analysis
493
9.4
Statistical Analysis for Terminating Simulations
497
9.4.1
Estimating Means
498
9.4.2
Estimating Other Measures of Performance
507
9.4.3
Choosing Initial Conditions
510
9.5
Statistical Analysis for Steady-State Parameters
511
9.5.1
The Problem of the Initial Transient
511
9.5.2
Replication/Deletion Approach for Means
523
9.5.3
Other Approaches for Means
526
9.5.4
Estimating Other Measures of Performance
540
9.6
Statistical Analysis for Steady-State Cycle Parameters
542
9.7
Multiple Measures of Performance
545
9.8
Time Plots of Important Variables
548
Appendix 9A: Ratios of Expectations and Jackknife
Estimators
550
Problems
551
Chapter
10
Comparing Alternative System Configurations
556
10.1
Introduction
556
10.2
Confidence Intervals for the Difference between the
Expected Responses of Two Systems
560
10.2.1
A Paired-ŕ
Confidence Interval
560
CONTENTS Xl
10.2.2
A Modified
Two-Sample-í
Confidence Interval
562
10.2.3
Contrasting the Two Methods
563
10.2.4
Comparisons Based on Steady-State Measures
of Performance
563
10.3
Confidence Intervals for Comparing More than Two Systems
565
10.3.1
Comparisons with a Standard
566
10.3.2
All Pairwise Comparisons
568
10.3.3
Multiple Comparisons with the Best
569
10.4
Ranking and Selection
569
10.4.1
Selecting the Best of
к
Systems
570
10.4.2
Selecting a Subset of Size
m
Containing the
Best of A: Systems
576
10.4.3
Additional Problems and Methods
577
Appendix 10A: Validity of the Selection Procedures
582
Appendix 10B: Constants for the Selection Procedures
583
Problems
584
Chapter
11
Variance-Reduction Techniques
587
11.1
Introduction
587
11.2
Common Random Numbers
588
11.2.1
Rationale
589
11.2.2
Applicability
590
11.2.3
Synchronization
592
11.2.4
Some Examples
596
11.3
Antithetic
Variâtes
604
11.4
Control
Variâtes
610
11.5
Indirect Estimation
617
11.6
Conditioning
619
Problems
623
Chapter
12
Experimental Design and Optimization
629
12.1
Introduction
629
12.2 2*
Factorial Designs
632
12.3
2k
~ľ
Fractional Factorial Designs
649
12.4
Response Surfaces and Metamodels
656
12.4.1
Introduction and Analysis of the Inventory Model
657
12.4.2
Analysis of the Predator-Prey Model
668
12.4.3
Space-Filling Designs and Kriging
671
12.5
Simulation-Based Optimization
679
12.5.1
Optimum-Seeking Methods
681
12.5.2
Optimum-Seeking Packages Interfaced with
Simulation Software
682
Problems
690
Xli CONTENTS
Chapter
13
Agent-Based Simulation and System Dynamics
693
13.1
Introduction
693
13.2
Agent-Based Simulation
694
13.2.1
Detailed Examples
699
13.2.2
Time-Advance Mechanisms for
ABS 704
13.2.3
Summary of
ABS 707
13.3
Continuous Simulation
707
13.3.1
System Dynamics
708
13.4
Combined Discrete-Continuous Simulation
713
13.5
Monte Carlo Simulation
714
13.6
Spreadsheet Simulation
717
Problems
719
Chapter
14
Simulation of Manufacturing Systems website chapter
Appendix
721
References
725
Index
759
|
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| id | DE-604.BV041773819 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T01:05:05Z |
| institution | BVB |
| isbn | 9780073401324 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027219750 |
| oclc_num | 878930506 |
| open_access_boolean | |
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| physical | XVIII, 776, [4] S. Ill., graph. Darst. |
| publishDate | 2015 |
| publishDateSearch | 2015 |
| publishDateSort | 2015 |
| publisher | McGraw Hill Education |
| record_format | marc |
| spelling | Law, Averill M. Verfasser (DE-588)170238075 aut Simulation modeling and analysis Averill M. Law 5. ed. Boston [u.a.] McGraw Hill Education 2015 XVIII, 776, [4] S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Digital computer simulation Computersimulation (DE-588)4148259-1 gnd rswk-swf Computersimulation (DE-588)4148259-1 s DE-604 Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027219750&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Law, Averill M. Simulation modeling and analysis Digital computer simulation Computersimulation (DE-588)4148259-1 gnd |
| subject_GND | (DE-588)4148259-1 |
| title | Simulation modeling and analysis |
| title_auth | Simulation modeling and analysis |
| title_exact_search | Simulation modeling and analysis |
| title_full | Simulation modeling and analysis Averill M. Law |
| title_fullStr | Simulation modeling and analysis Averill M. Law |
| title_full_unstemmed | Simulation modeling and analysis Averill M. Law |
| title_short | Simulation modeling and analysis |
| title_sort | simulation modeling and analysis |
| topic | Digital computer simulation Computersimulation (DE-588)4148259-1 gnd |
| topic_facet | Digital computer simulation Computersimulation |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027219750&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT lawaverillm simulationmodelingandanalysis |