Simulation modeling and analysis:
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York u.a.
McGraw-Hill
1991
|
| Ausgabe: | 2. ed. |
| Schriftenreihe: | McGraw-Hill series in industrial engineering und management science
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Inhaltsverzeichnis |
| Beschreibung: | XXII, 759 S.: graph. Darst. |
| ISBN: | 0070366985 |
Internformat
MARC
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| 245 | 1 | 0 | |a Simulation modeling and analysis |c Averill M. Law ; W. David Kelton |
| 250 | |a 2. ed. | ||
| 264 | 1 | |a New York u.a. |b McGraw-Hill |c 1991 | |
| 300 | |a XXII, 759 S.: graph. Darst. | ||
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Datensatz im Suchindex
| _version_ | 1804120041851977728 |
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| adam_text | Titel: Simulation modeling and analysis
Autor: Law, Averill M
Jahr: 1991
CONTENTS List of Symbols xvii Preface to the Second Edition xix Preface to the First Edition xxi Chapter 1 Basic Simulation Modeling 1 l.i The Nature of Simulation 1 1.2 Systems, Models, and Simulation 3 1.3 Discrete-Event Simulation 7 1.3.1 Time-Advance Mechanisms 1.3.2 Components and Organization of a Discrete-Event 8 Simulation Model 10 1.4 Simulation of a Single-Server Queueing System 13 1.4.1 Problem Statement 13 1.4.2 Intuitive Explanation 19 1.4.3 Program Organization and Logic 29 1.4.4 FORTRAN Program 34 1.4.5 Pascal Program 44 1.4.6 C Program 52 1.4.7 Simulation Output and Discussion 60 1.4.8 Alternative Stopping Rules 62 1.4.9 Determining the Events and Variables 72 1.5 Simulation of an Inventory System 75 1.5.1 Problem Statement 75 1.5.2 Program Organization and Logic 77 1.5.3 FORTRAN Program 82 1.5.4 Pascal Program 89 1.5.5 C Program .96 1.5.6 Simulation Output and Discussion 102 1.6 Distributed Simulation 103 1.7 Steps in a Simulation Study 106 1.8 Other Types of Simulation 109 ix
109 112 113 114 116 118 118 119 120 122 123 130 133 133 134 134 135 141 150 150 150 156 157 158 158 169 170 170 171 183 185 185 187 199 200 202 215 232 234 234 235 1.8.1 Continuous Simulation 1.8.2 Combined Discrete-Continuous Simulation 1.8.3 Monte Carlo Simulation Advantages, Disadvantages, and Pitfalls of Simulation Appendix 1A: Fixed-Increment Time Advance Appendix IB: A Primer on Queueing Systems 1B.1 Components of a Queueing System IB.2 Notation for Queueing Systems IB.3 Measures of Performance for Queueing Systems Appendix 1C: Notes on the Computers and Compilers Used Problems References Modeling Complex Systems Introduction List Processing in Simulation 2.2.1 Approaches to Storing Lists in a Computer 2.2.2 Linked Storage Allocation __ A Simple Simulation Language, SIMLIB Single-Server Queueing Simulation with SIMLIB 2.4.1 Problem Statement 2.4.2 SIMLIB Program 2.4.3 Simulation Output and Discussion Time-Shared Computer Model 2.5.1 Problem Statement 2.5.2 SIMLIB Program 2.5.3 Simulation Output and Discussion Multiteller Bank with Jockeying 2.6.1 Problem Statement 2.6.2 SIMLIB Program 2.6.3 Simulation Output and Discussion Job-Shop Model 2.7.1 Problem Statement 2.7.2 SIMLIB Program 2.7.3 Simulation Output and Discussion Efficient Event-List Manipulation Appendix 2A: FORTRAN Code for SIMLIB Problems References Simulation Software Introduction Comparison of Simulation Languages with General-Purpose Languages
CONTENTS xi 3.3 Classification of Simulation Software 236 3.3.1 Simulation Languages vs. Simulators 236 3.3.2 Modeling Approaches 237 3.3.3 Common Modeling Elements 240 3.4 Desirable Software Features 240 3.4.1 General Features 240 3.4.2 Animation 241 3.4.3 Statistical Capabilities 242 3.4.4 Customer Support 243 3.4.5 Output Reports 243 3.5 GPSS 243 3.5.1 GPSS/H 244 3.5.2 Simulation of the MIMIl Queue 244 3.5.3 GPSS/PC 248 3.6 SIMAN/Cinema 248 3.6.1 Simulation of the MIMIl Queue 249 3.7 SIMSCRIPTII.5 252 3.7.1 Simulation of the MIMIl Queue 254 3.8 SLAM II and Related Software 258 3.8.1 Simulation of the MIMIl Queue 259 3.9 Comparison of Simulation Languages 263 3.10 Additional Simulation Software 265 References 266 Chapter 4 Review of Basic Probability and Statistics 267 4.1 Introduction 267 4.2 Random Variables and Their Properties 268 4.3 Simulation Output Data and Stochastic Processes 279 4.4 Estimation of Means, Variances, and Correlations 282 4.5 Confidence Intervals and Hypothesis Tests for the Mean 286 4.6 The Strong Law of Large Numbers 292 4.7 The Danger of Replacing a Probability Distribution by Its Mean 292 Appendix 4A: Comments on Covariance-Stationary Processes 293 Problems 294 References 297 Chapter 5 Building Valid and Credible Simulation Models 298 5.1 Introduction and Definitions 298 5.2 Some Principles of Valid Simulation Modeling 300 5.3 Verification of Simulation Computer Programs 302 5.4 General Perspectives on Validation 306
307 308 310 311 314 315 319 321 322 323 325 325 329 329 329 343 350 353 356 358 360 363 367 372 372 380 394 400 403 405 405 406 409 409 411 413 417 420 420 A Three-Step Approach for Developing Valid and Credible Simulation Models 5.5.1 Develop a Model with High Face Validity 5.5.2 Test the Assumptions of the Model Empirically 5.5.3 Determine How Representative the Simulation Output Data Are Statistical Procedures for Comparing Real-World Observations and Simulation Output Data 5.6.1 Inspection Approach 5.6.2 Confidence-Interval Approach Based on Independent Data 5.6.3 Time-Series Approaches Problems References Selecting Input Probability Distributions Introduction Useful Probability Distributions 6.2.1 Parameterization of Continuous Distributions 6.2.2 Continuous Distributions 6.2.3 Discrete Distributions — 6.2.4 Empirical Distributions Techniques for Assessing Sample Independence Activity I: Hypothesizing Families of Distributions _ 6.4.1 Summary Statistics 6.4.2 Histograms and Line Graphs 6.4.3 Quantile Summaries and Box Plots Activity II: Estimation of Parameters Activity III: Determining How Representative the Fitted Distributions Are 6.6.1 Heuristic Procedures 6.6.2 Goodness-of-Fit Tests An Extended Example Shifted and Truncated Distributions Selecting a Distribution in the Absence of Data Models of Arrival Processes 6.10.1 Poisson Processes 6.10.2 Nonstationary Poisson Processes 6.10.3 Batch Arrivals Assessing the Homogeneity of Different Data Sets Appendix 6A: Tables of MLEs for the Gamma and Beta Distributions Problems References Random-Number Generators Introduction
CONTENTS xiii 7.2 Linear Congruential Generators 424 7.2.1 Mixed Generators 427 7.2.2 Multiplicative Generators 428 7.3 Other Kinds of Generators 431 7.3.1 More General Congruences 432 7.3.2 Composite Generators 433 7.3.3 Tausworthe and Related Generators 434 7.4 Testing Random-Number Generators 436 7.4.1 Empirical Tests 436 7.4.2 Theoretical Tests 442 7.4.3 Some General Observations on Testing 447 7.5 Random-Number Generation on Microcomputers 447 7.6 Generators Used by Simulation Languages 448 Appendix 7A: Portable Computer Codes 449 7A.1 FORTRAN 449 7A.2 Pascal 451 7A.3 C 454 7A.4 Obtaining Initial Seeds for the Streams 456 Problems 457 References 459 Chapter 8 Generating Random Variates 462 8.1 Introduction 462 8.2 General Approaches to Generating Random Variates 465 8.2.1 Inverse Transform 465 8.2.2 Composition 474 8.2.3 Convolution 477 8.2.4 Acceptance-Rejection 478 8.2.5 Special Properties 484 8.3 Generating Continuous Random Variates 485 8.3.1 Uniform 485 8.3.2 Exponential 486 8.3.3 m -Erlang 486 8.3.4 Gamma 487 8.3.5 Weibull 490 8.3.6 Normal 490 8.3.7 Lognormal 492 8.3.8 Beta 492 8.3.9 Pearson Type V 493 8.3.10 Pearson Type VI 494 8.3.11 Triangular 494 8.3.12 Empirical Distributions 494 8.4 Generating Discrete Random Variates 496 8.4.1 Bernoulli 496 8.4.2 Discrete Uniform 497 8.4.3 Arbitrary Discrete Distribution 497
xiv CONTENTS 8.4.4 Binomial 502 8.4.5 Geometric 502 8.4.6 Negative Binomial 502 8.4.7 Poisson 503 8.5 Generating Correlated Random Variates 504 8.5.1 Using Conditional Distributions 504 8.5.2 Multivariate Normal and Multivariate Lognormal 505 8.5.3 Correlated Gamma Random Variates 506 8.6 Generating Arrival Processes 507 8.6.1 Poisson Processes 507 8.6.2 Nonstationary Poisson Processes 507 8.6.3 Batch Arrivals 510 Appendix 8A: Validity of the Acceptance-Rejection Method 512 Appendix 8B: Setup for the Alias Method 513 Problems 514 References 518 Chapter 9 Output Data Analysis for a Single System 522 9.1 Introduction 522 9.2 Transient and Steady-State Behavior of a Stochastic Process 525 9.3 Types of Simulations with Regard to Output Analysis 527 9.4 Statistical Analysis for Terminating Simulations 532 9.4.1 Estimating Means 532 9.4.2 Estimating Other Measures of Performance 540 9.4.3 Choosing Initial Conditions 543 9.5 Statistical Analysis for Steady-State Parameters 544 9.5.1 The Problem of the Initial Transient 545 9.5.2 Replication/Deletion Approach for Means 551 9.5.3 Other Approaches for Means 553 9.5.4 Estimating Other Measures of Performance 564 9.6 Statistical Analysis for Steady-State Cycle Parameters 565 9.7 Multiple Measures of Performance 568 9.8 Time Plots of Important Variables 572 Appendix 9A: Ratios of Expectations and Jackknife Estimators 572 Problems 575 References 579 Chapter 10 Comparing Alternative System Configurations 582 10.1 Introduction 582 10.2 Confidence Intervals for the Difference between Performance Measures of Two Systems 586 10.2.1 A Paired-i Confidence Interval 587
CONTENTS XV 10.2.2 A Modified Two-Sample-i Confidence Interval 588 10.2.3 Contrasting the Two Methods 589 10.2.4 Comparisons Based on Steady-State Measures of Performance 590 10.3 Confidence Intervals for Comparing More Than Two Systems 591 10.3.1 Comparisons with a Standard 592 10.3.2 All Pairwise Comparisons 594 10.4 Ranking and Selection 595 10.4.1 Selecting the Best of k Systems 596 10.4.2 Selecting a Subset of Size m Containing the Best of k Systems 598 10.4.3 Selecting the m Best of k Systems 600 10.4.4 Additional Problems and Methods 601 Appendix 10A: Validity of the Selection Procedures 604 Appendix 10B: Constants for the Selection Procedures 606 Problems 607 References 609 Chapter 11 Variance-Reduction Techniques 612 11.1 Introduction 612 11.2 Common Random Numbers 613 11.2.1 Rationale 613 11.2.2 Applicability 615 11.2.3 Synchronization 617 11.2.4 Some Examples 620 11.3 Antithetic Variates 628 11.4 Control Variates 634 11.5 Indirect Estimation 641 11.6 Conditioning 644 Problems 648 References 652 Chapter 12 Experimental Design and Optimization 656 12.1 Introduction 656 12.2 2 k Factorial Designs 659 12.3 Coping with Many Factors 670 12.3.1 2 k ~ p Fractional Factorial Designs 670 12.3.2 Factor-Screening Strategies 677 12.4 Response Surfaces and Metamodels 679 12.5 Gradient Estimation 689 Problems 691 References 693 Chapter 13 Simulation of Manufacturing Systems 696 13.1 Introduction 696 13.2 Objectives of Simulation in Manufacturing 697
699 703 703 705 713 713 723 725 725 726 726 727 729 732 733 735 737 741 743 749 Simulation Software for Manufacturing Applications Modeling System Randomness 13.4.1 Sources of Randomness 13.4.2 Machine Downtimes An Extended Example 13.5.1 Problem Description and Simulation Results 13.5.2 Statistical Calculations A Simulation Case Study of a Metal-Parts Manufacturing Facility 13.6.1 Description of the System 13.6.2 Overall Objectives and Issues to Be Investigated 13.6.3 Development of the Model 13.6.4 Model Verification and Validation 13.6.5 Results of the Simulation Experiments 13.6.6 Conclusions and Benefits Problems References Appendix INDEXES Author Index Subject Index
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| spelling | Law, Averill M. Verfasser (DE-588)170238075 aut Simulation modeling and analysis Averill M. Law ; W. David Kelton 2. ed. New York u.a. McGraw-Hill 1991 XXII, 759 S.: graph. Darst. txt rdacontent n rdamedia nc rdacarrier McGraw-Hill series in industrial engineering und management science Computersimulation (DE-588)4148259-1 gnd rswk-swf Computersimulation (DE-588)4148259-1 s DE-604 Kelton, W. David Verfasser (DE-588)170238059 aut http://www3.ub.tu-berlin.de/ihv/000096160.pdf Inhaltsverzeichnis HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=003664174&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
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| 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 ; W. David Kelton |
| title_fullStr | Simulation modeling and analysis Averill M. Law ; W. David Kelton |
| title_full_unstemmed | Simulation modeling and analysis Averill M. Law ; W. David Kelton |
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