Simulation:
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Amsterdam [u.a.]
Elsevier, NH
2006
|
| Ausgabe: | 1. ed. |
| Schriftenreihe: | Handbooks in operations research and management science
13 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIII, 678 S. graph. Darst. |
| ISBN: | 0444514287 9780444514288 |
Internformat
MARC
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Datensatz im Suchindex
| _version_ | 1804135588275683328 |
|---|---|
| adam_text | Contents
Dedication v
CHAPTER 1
Stochastic Computer Simulation
Shane G. Henderson and Barry L. Nelson 1
1 Scope of the Handbook 1
2 Key concepts in stochastic simulation 4
3 Organization of the Handbook 17
Acknowledgements ] 8
References 18
CHAPTER 2
Mathematics for Simulation
Shane G. Henderson 19
1 Introduction 19
2 Static simulation: Activity networks 21
3 A model of ambulance operations 27
4 Finite horizon performance 28
5 Steady state simulation 34
Acknowledgements 50
Appendix: Proof of Proposition 15 50
References 52
CHAPTER 3
Uniform Random Number Generation
Pierre LEcuyer 55
1 Introduction 55
2 Uniform random number generators 5(
3 Linear recurrences modulo in Ml
4 Generators based on recurrences modulo 2 M
5 Nonlinear RNGs 75
6 Empirical statistical tests 76
7 Conclusion, future work and open issues 77
Acknowledgements 78
References 78
vii
viii Contents
CHAPTER 4
Nonuniform Random Variate Generation
Luc Devroye 83
1 The main paradigms 83
2 Uniformly bounded times 94
3 Universal generators 97
4 Indirect problems 99
5 Random processes 107
6 Markov chain methodology 108
Acknowledgement 116
References 116
CHAPTER 5
Multivariate Input Processes
Bahar Biller and Soumyadip Ghosh 123
1 Introduction 123
2 Constructing full joint distributions 126
3 Parametric families of joint distributions 133
4 Constructing partially specified joint distributions 136
5 Conclusion 149
References 150
CHAPTER 6
Arrival Processes, Random Lifetimes and Random Objects
Lawrence M. Leemis 155
1 Arrival processes 155
2 Generating random lifetimes 167
3 Generating random objects 172
Acknowledgements 178
References 178
CHAPTER 7
Implementing Representations of Uncertainty
W. David Kelton 181
1 Introduction 181
2 Random number generation 182
3 Random structure generation 184
4 Application to variance reduction 186
5 Conclusions and suggestions 189
References 191
CHAPTER 8
Statistical Estimation in Computer Simulation
Christos Alexopoulos 193
1 Introduction 193
2 Background 195
Contents ix
3 Sample averages and time averages 196
4 Stationary processes 199
5 Analyzing data from independent replications 204
6 Density estimation 210
7 Summary 220
Acknowledgements 222
References 222
CHAPTER 9
Subjective Probability and Bayesian Methodology
Stephen E. Chick 225
Introduction 225
1 Main concepts 227
2 Computational issues 237
3 Input distribution and model selection 239
4 Joint input output models 240
5 Ranking and selection 245
6 Discussion and future directions 252
Acknowledgement 253
References 253
CHAPTER 10
A Hilbert Space Approach to Variance Reduction
Roberto Szechtman 259
1 Introduction 259
2 Problem formulation and basic results 260
3 Hilbert spaces 263
4 A Hilbert space approach to control variates 27 i
5 Conditional Monte Carlo in Hilbert space 273
6 Control variates and conditional Monte Carlo from a Hilbert space perspective 274
7 Weighted Monte Carlo 275
8 Stratification techniques 278
9 Latin hypercube sampling 281
10 A numerical example 286
11 Conclusions 287
Acknowledgements 288
References 288
CHAPTER 11
Rare Event Simulation Techniques: An Introduction and Recent
Advances
S. Juneja and P. Shahabuddin 291
1 Introduction 291
2 Rare event simulation and importance sampling 296
3 Rare event simulation in a Markovian framework 302
4 Large deviations of multidimensional random walks 309
x Contents
5 Adaptive importance sampling techniques 316
6 Queueing systems 327
7 Heavy tailed simulations 330
8 Financial engineering applications 335
Acknowledgement 346
References 346
CHAPTER 12
Quasi Random Number Techniques
C. Lemieux 351
1 Introduction 351
2 An example 356
3 A key concept: Effective dimension 359
4 Constructing quasi random point sets 364
5 Recurrence based point sets 369
6 Randomization techniques and variance results 371
7 Combination with other variance reduction techniques 374
8 Future directions 375
Acknowledgements 376
References 376
CHAPTER 13
Analysis for Design
Ward Whitt 381
1 Introduction 381
2 The standard statistical framework 385
3 The asymptotic parameters for a function of a Markov chain 393
4 Birth and death examples 397
5 Diffusion processes 401
6 Stochastic process limits 405
7 Deleting an initial portion of the run to reduce bias 410
8 Directions for further research 411
Acknowledgement 411
References 411
CHAPTER 14
Resampling Methods
R.C.H. Cheng 415
1 Introduction 415
2 The bootstrap 417
3 Quantiles and confidence intervals 422
4 Theory 428
5 Simulation models 436
6 Bootstrap comparisons 443
7 Bayesian models 446
Contents xi
8 Time series output 448
9 Final comments 451
References 451
CHAPTER 15
Correlation Based Methods for Output Analysis
David Goldsman and Barry L. Nelson 455
1 Introduction 455
2 Motivation 457
3 Estimators using nonoverlapping batches 459
4 Estimators from overlapping batches 468
5 Summary and conclusions 473
Acknowledgement 474
References 474
CHAPTER 16
Simulation Algorithms for Regenerative Processes
Peter W. Glynn 477
1 Introduction 477
2 The steady state simulation problem 478
3 The regenerative estimator for the TAVC 480
4 Choice of the optimal regeneration state 483
5 The regenerative approach to the initial transient and initial bias problems 484
6 When is a simulation regenerative? 487
7 When is a GSMP regenerative? 489
8 Algorithmic identification of regenerative structure 490
9 A martingale perspective on regeneration 493
10 Efficiency improvement via regeneration: Computing steady state gradients 496
11 Efficiency improvement via regeneration: Computing infinite horizon discounted
reward 498
References 499
CHAPTER 17
Selecting the Best System
Seong Hee Kim and Barry L. Nelson 501
1 Introduction 501
2 Basics of ranking and selection 502
3 Simulation issues and key results 508
4 Example procedures 517
5 Application 521
6 Asymptotic analysis 522
7 Other formulations 526
8 Future directions 53]
Acknowledgements 532
References 532
xii Contents
CHAPTER 18
Metamodel Based Simulation Optimization
Russell R. Barton and Martin Meckesheimer 535
1 Introduction 535
2 Metamodels and simulation 538
3 Metamodel based optimization 545
4 Response surface methodology (RSM) 548
5 Global metamodel based optimization 563
6 Summary 569
Acknowledgements 570
References 570
CHAPTER 19
Gradient Estimation
Michael C. Fu 575
1 Introduction 575
2 Gradient based simulation optimization 577
3 Indirect gradient estimation 580
4 Direct gradient estimation 583
5 Examples 598
6 Basic theoretical tools 605
7 Simple guidelines for the simulation practitioner 606
8 Applications 607
9 Probing further 609
10 Future research directions 611
Acknowledgements 612
References 612
CHAPTER 20
An Overview of Simulation Optimization via Random Search
Sigrun Andradottir 617
1 Introduction 617
2 A brief review of random search methods 619
3 Convergence 621
4 Efficiency 624
5 Summary 629
Acknowledgements 630
References 630
CHAPTER 21
Metaheuristics
Sigurdur Olafsson 633
1 Introduction 633
2 Background to metaheuristics 635
3 Accounting for simulation noise 640
Contents xiii
4 Genetic algorithm 643
5 Tabu search 644
6 The nested partition method 646
7 Making convergence statements 647
8 Future directions 652
References 653
Author Index 655
Subject Index 667
|
| adam_txt |
Contents
Dedication v
CHAPTER 1
Stochastic Computer Simulation
Shane G. Henderson and Barry L. Nelson 1
1 Scope of the Handbook 1
2 Key concepts in stochastic simulation 4
3 Organization of the Handbook 17
Acknowledgements ] 8
References 18
CHAPTER 2
Mathematics for Simulation
Shane G. Henderson 19
1 Introduction 19
2 Static simulation: Activity networks 21
3 A model of ambulance operations 27
4 Finite horizon performance 28
5 Steady state simulation 34
Acknowledgements 50
Appendix: Proof of Proposition 15 50
References 52
CHAPTER 3
Uniform Random Number Generation
Pierre LEcuyer 55
1 Introduction 55
2 Uniform random number generators 5(
3 Linear recurrences modulo in Ml
4 Generators based on recurrences modulo 2 M
5 Nonlinear RNGs 75
6 Empirical statistical tests 76
7 Conclusion, future work and open issues 77
Acknowledgements 78
References 78
vii
viii Contents
CHAPTER 4
Nonuniform Random Variate Generation
Luc Devroye 83
1 The main paradigms 83
2 Uniformly bounded times 94
3 Universal generators 97
4 Indirect problems 99
5 Random processes 107
6 Markov chain methodology 108
Acknowledgement 116
References 116
CHAPTER 5
Multivariate Input Processes
Bahar Biller and Soumyadip Ghosh 123
1 Introduction 123
2 Constructing full joint distributions 126
3 Parametric families of joint distributions 133
4 Constructing partially specified joint distributions 136
5 Conclusion 149
References 150
CHAPTER 6
Arrival Processes, Random Lifetimes and Random Objects
Lawrence M. Leemis 155
1 Arrival processes 155
2 Generating random lifetimes 167
3 Generating random objects 172
Acknowledgements 178
References 178
CHAPTER 7
Implementing Representations of Uncertainty
W. David Kelton 181
1 Introduction 181
2 Random number generation 182
3 Random structure generation 184
4 Application to variance reduction 186
5 Conclusions and suggestions 189
References 191
CHAPTER 8
Statistical Estimation in Computer Simulation
Christos Alexopoulos 193
1 Introduction 193
2 Background 195
Contents ix
3 Sample averages and time averages 196
4 Stationary processes 199
5 Analyzing data from independent replications 204
6 Density estimation 210
7 Summary 220
Acknowledgements 222
References 222
CHAPTER 9
Subjective Probability and Bayesian Methodology
Stephen E. Chick 225
Introduction 225
1 Main concepts 227
2 Computational issues 237
3 Input distribution and model selection 239
4 Joint input output models 240
5 Ranking and selection 245
6 Discussion and future directions 252
Acknowledgement 253
References 253
CHAPTER 10
A Hilbert Space Approach to Variance Reduction
Roberto Szechtman 259
1 Introduction 259
2 Problem formulation and basic results 260
3 Hilbert spaces 263
4 A Hilbert space approach to control variates 27 i
5 Conditional Monte Carlo in Hilbert space 273
6 Control variates and conditional Monte Carlo from a Hilbert space perspective 274
7 Weighted Monte Carlo 275
8 Stratification techniques 278
9 Latin hypercube sampling 281
10 A numerical example 286
11 Conclusions 287
Acknowledgements 288
References 288
CHAPTER 11
Rare Event Simulation Techniques: An Introduction and Recent
Advances
S. Juneja and P. Shahabuddin 291
1 Introduction 291
2 Rare event simulation and importance sampling 296
3 Rare event simulation in a Markovian framework 302
4 Large deviations of multidimensional random walks 309
x Contents
5 Adaptive importance sampling techniques 316
6 Queueing systems 327
7 Heavy tailed simulations 330
8 Financial engineering applications 335
Acknowledgement 346
References 346
CHAPTER 12
Quasi Random Number Techniques
C. Lemieux 351
1 Introduction 351
2 An example 356
3 A key concept: Effective dimension 359
4 Constructing quasi random point sets 364
5 Recurrence based point sets 369
6 Randomization techniques and variance results 371
7 Combination with other variance reduction techniques 374
8 Future directions 375
Acknowledgements 376
References 376
CHAPTER 13
Analysis for Design
Ward Whitt 381
1 Introduction 381
2 The standard statistical framework 385
3 The asymptotic parameters for a function of a Markov chain 393
4 Birth and death examples 397
5 Diffusion processes 401
6 Stochastic process limits 405
7 Deleting an initial portion of the run to reduce bias 410
8 Directions for further research 411
Acknowledgement 411
References 411
CHAPTER 14
Resampling Methods
R.C.H. Cheng 415
1 Introduction 415
2 The bootstrap 417
3 Quantiles and confidence intervals 422
4 Theory 428
5 Simulation models 436
6 Bootstrap comparisons 443
7 Bayesian models 446
Contents xi
8 Time series output 448
9 Final comments 451
References 451
CHAPTER 15
Correlation Based Methods for Output Analysis
David Goldsman and Barry L. Nelson 455
1 Introduction 455
2 Motivation 457
3 Estimators using nonoverlapping batches 459
4 Estimators from overlapping batches 468
5 Summary and conclusions 473
Acknowledgement 474
References 474
CHAPTER 16
Simulation Algorithms for Regenerative Processes
Peter W. Glynn 477
1 Introduction 477
2 The steady state simulation problem 478
3 The regenerative estimator for the TAVC 480
4 Choice of the optimal regeneration state 483
5 The regenerative approach to the initial transient and initial bias problems 484
6 When is a simulation regenerative? 487
7 When is a GSMP regenerative? 489
8 Algorithmic identification of regenerative structure 490
9 A martingale perspective on regeneration 493
10 Efficiency improvement via regeneration: Computing steady state gradients 496
11 Efficiency improvement via regeneration: Computing infinite horizon discounted
reward 498
References 499
CHAPTER 17
Selecting the Best System
Seong Hee Kim and Barry L. Nelson 501
1 Introduction 501
2 Basics of ranking and selection 502
3 Simulation issues and key results 508
4 Example procedures 517
5 Application 521
6 Asymptotic analysis 522
7 Other formulations 526
8 Future directions 53]
Acknowledgements 532
References 532
xii Contents
CHAPTER 18
Metamodel Based Simulation Optimization
Russell R. Barton and Martin Meckesheimer 535
1 Introduction 535
2 Metamodels and simulation 538
3 Metamodel based optimization 545
4 Response surface methodology (RSM) 548
5 Global metamodel based optimization 563
6 Summary 569
Acknowledgements 570
References 570
CHAPTER 19
Gradient Estimation
Michael C. Fu 575
1 Introduction 575
2 Gradient based simulation optimization 577
3 Indirect gradient estimation 580
4 Direct gradient estimation 583
5 Examples 598
6 Basic theoretical tools 605
7 Simple guidelines for the simulation practitioner 606
8 Applications 607
9 Probing further 609
10 Future research directions 611
Acknowledgements 612
References 612
CHAPTER 20
An Overview of Simulation Optimization via Random Search
Sigrun Andradottir 617
1 Introduction 617
2 A brief review of random search methods 619
3 Convergence 621
4 Efficiency 624
5 Summary 629
Acknowledgements 630
References 630
CHAPTER 21
Metaheuristics
Sigurdur Olafsson 633
1 Introduction 633
2 Background to metaheuristics 635
3 Accounting for simulation noise 640
Contents xiii
4 Genetic algorithm 643
5 Tabu search 644
6 The nested partition method 646
7 Making convergence statements 647
8 Future directions 652
References 653
Author Index 655
Subject Index 667 |
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| index_date | 2024-07-02T15:28:30Z |
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| series | Handbooks in operations research and management science |
| series2 | Handbooks in operations research and management science |
| spelling | Simulation ed. by Shane G. Henderson ... 1. ed. Amsterdam [u.a.] Elsevier, NH 2006 XIII, 678 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Handbooks in operations research and management science 13 Computersimulaties gtt Gestion - Simulation, Méthodes de Management gtt Simulation par ordinateur Simulação larpcal Systèmes stochastiques Computer simulation Management Simulation methods Stochastic systems Computersimulation (DE-588)4148259-1 gnd rswk-swf Operations Research (DE-588)4043586-6 gnd rswk-swf Computersimulation (DE-588)4148259-1 s Operations Research (DE-588)4043586-6 s DE-604 Henderson, Shane G. Sonstige (DE-588)138172412 oth Handbooks in operations research and management science 13 (DE-604)BV002805695 13 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014951386&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Simulation Handbooks in operations research and management science Computersimulaties gtt Gestion - Simulation, Méthodes de Management gtt Simulation par ordinateur Simulação larpcal Systèmes stochastiques Computer simulation Management Simulation methods Stochastic systems Computersimulation (DE-588)4148259-1 gnd Operations Research (DE-588)4043586-6 gnd |
| subject_GND | (DE-588)4148259-1 (DE-588)4043586-6 |
| title | Simulation |
| title_auth | Simulation |
| title_exact_search | Simulation |
| title_exact_search_txtP | Simulation |
| title_full | Simulation ed. by Shane G. Henderson ... |
| title_fullStr | Simulation ed. by Shane G. Henderson ... |
| title_full_unstemmed | Simulation ed. by Shane G. Henderson ... |
| title_short | Simulation |
| title_sort | simulation |
| topic | Computersimulaties gtt Gestion - Simulation, Méthodes de Management gtt Simulation par ordinateur Simulação larpcal Systèmes stochastiques Computer simulation Management Simulation methods Stochastic systems Computersimulation (DE-588)4148259-1 gnd Operations Research (DE-588)4043586-6 gnd |
| topic_facet | Computersimulaties Gestion - Simulation, Méthodes de Management Simulation par ordinateur Simulação Systèmes stochastiques Computer simulation Management Simulation methods Stochastic systems Computersimulation Operations Research |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014951386&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV002805695 |
| work_keys_str_mv | AT hendersonshaneg simulation |