Simulation modeling and analysis
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| Format: | Buch |
| Sprache: | English |
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Boston [u.a.]
McGraw Hill
2007
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| Ausgabe: | 4. ed., internat. ed. |
| Schriftenreihe: | McGraw-Hill series in industrial engineering and management science
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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 4. ed., internat. ed. | ||
| 264 | 1 | |a Boston [u.a.] |b McGraw Hill |c 2007 | |
| 300 | |a XIX, 768 S. |b Ill., graph. Darst. |e 1 CD-ROM (12 cm) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a McGraw-Hill series in industrial engineering and management science | |
| 650 | 4 | |a Computersimulation - Lehrbuch | |
| 650 | 4 | |a Computersimulation - Stochastik - Lehrbuch | |
| 650 | 4 | |a Digital computer simulation | |
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| 689 | 0 | 0 | |a Computersimulation |0 (DE-588)4148259-1 |D s |
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| adam_text | SIMULATION MODELING AND ANALYSIS * : . . *K^ I -S*. ; */,.ISR ;
:^-W *.»V . I -I.-, .--; I -.*.*. * .. .;** !;**..**; . .,. :,S :
.Y.--,: ,.-:.V: : FOURTH EDITION AVERILL M. LAW PRESIDENT AVERILL M.
LAW & ASSOCIATES, INC. TUCSON, ARIZONA, USA WWW.AVERILL-LAW.COM BOSTON
BURR RIDGE, IL DUBUQUE, IA MADISON, WL NEW YORK SAN FRANCISCO ST. LOUIS
BANGKOK BOGOTA CARACAS KUALA LUMPUR LISBON LONDON MADRID MEXICO CITY
MILAN MONTREAL NEW DELHI SANTIAGO SEOUL SINGAPORE SYDNEY TAIPEI TORONTO
CONTENTS LIST OF SYMBOLS XV PREFACE XVII 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 C 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 C
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 1.7 STEPS IN A SOUND SIMULATION STUDY 66 1.8 OTHER TYPES
OF SIMULATION 70 1.8.1 CONTINUOUS SIMULATION 70 1.8.2 COMBINED
DISCRETE-CONTINUOUS SIMULATION 72 1.8.3 MONTE CARLO SIMULATION 73 1.8.4
SPREADSHEET SIMULATION 74 VLL VLLL CONTENTS 1.9 ADVANTAGES,
DISADVANTAGES, AND PITFALLS OF SIMULATION 76 APPENDIX 1A:
FIXED-INCREMENT TIME ADVANCE 78 APPENDIX 1B: A PRIMER ON QUEUEING
SYSTEMS 79 1B.1 COMPONENTS OF A QUEUEING SYSTEM 80 IB.2 NOTATION FOR
QUEUEING SYSTEMS 80 IB.3 MEASURES OF PERFORMANCE FOR QUEUEING SYSTEMS 81
PROBLEMS 84 CHAPTER 2 MODELING COMPLEX SYSTEMS 91 2.1 INTRODUCTION 91
2.2 LIST PROCESSING IN SIMULATION 92 2.2.1 APPROACHES TO STORING LISTS
IN A COMPUTER 92 2.2.2 LINKED STORAGE ALLOCATION 93 2.3 A SIMPLE
SIMULATION LANGUAGE: SIMLIB 99 2.4 SINGLE-SERVER QUEUEING SIMULATION
WITH SIMLIB 108 2.4.1 PROBLEM STATEMENT 108 2.4.2 SIMLIB PROGRAM 108
2.4.3 SIMULATION OUTPUT AND DISCUSSION 113 2.5 TIME-SHARED COMPUTER
MODEL 114 2.5.1 PROBLEM STATEMENT 114 2.5.2 SIMLIB PROGRAM 115 2.5.3
SIMULATION OUTPUT AND DISCUSSION 123 2.6 MULTITELLER BANK WITH JOCKEYING
126 2.6.1 PROBLEM STATEMENT 126 2.6.2 SIMLIB PROGRAM 127 2.6.3
SIMULATION OUTPUT AND DISCUSSION 137 2.7 JOB-SHOP MODEL 140 2.7.1
PROBLEM STATEMENT 140 2.7.2 SIMLIB PROGRAM 142 2.7.3 SIMULATION OUTPUT
AND DISCUSSION 153 2.8 EFFICIENT EVENT-LIST MANIPULATION 155 APPENDIX
2A: C CODE FOR SIMLIB 156 PROBLEMS 169 CHAPTER 3 SIMULATION SOFTWARE 187
3.1 INTRODUCTION 187 3.2 COMPARISON OF SIMULATION PACKAGES WITH
PROGRAMMING LANGUAGES 188 3.3 CLASSIFICATION OF SIMULATION SOFTWARE 189
3.3.1 GENERAL-PURPOSE VS. APPLICATION-ORIENTED SIMULATION PACKAGES 189
CONTENTS IX 3.3.2 MODELING APPROACHES 190 3.3.3 COMMON MODELING ELEMENTS
192 3.4 DESIRABLE SOFTWARE FEATURES 193 3.4.1 GENERAL CAPABILITIES 193
3.4.2 HARDWARE AND SOFTWARE REQUIREMENTS 195 3.4.3 ANIMATION AND DYNAMIC
GRAPHICS 195 3.4.4 STATISTICAL CAPABILITIES 197 3.4.5 CUSTOMER SUPPORT
AND DOCUMENTATION 198 3.4.6 OUTPUT REPORTS AND GRAPHICS 199 3.5
GENERAL-PURPOSE SIMULATION PACKAGES 200 3.5.1 ARENA 200 3.5.2 EXTEND 206
3.5.3 OTHER GENERAL-PURPOSE SIMULATION PACKAGES 211 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 228 4.5 CONFIDENCE INTERVALS AND
HYPOTHESIS TESTS FOR THE MEAN 232 4.6 THE STRONG LAW OF LARGE NUMBERS
237 4.7 THE DANGER OF REPLACING A PROBABILITY DISTRIBUTION BY ITS MEAN
238 APPENDIX 4A: COMMENTS ON COVARIANCE-STATIONARY PROCESSES 239
PROBLEMS 239 CHAPTER 5 BUILDING VALID, CREDIBLE, AND APPROPRIATELY
DETAILED SIMULATION MODELS 243 5.1 INTRODUCTION AND DEFINITIONS 243 5.2
GUIDELINES FOR DETERMINING THE LEVEL OF MODEL DETAIL 246 5.3
VERIFICATION OF SIMULATION COMPUTER PROGRAMS 248 5.4 TECHNIQUES FOR
INCREASING MODEL VALIDITY AND CREDIBILITY 253 5.4.1 COLLECT HIGH-QUALITY
INFORMATION AND DATA ON THE SYSTEM 253 5.4.2 INTERACT WITH THE MANAGER
ON A REGULAER BASIS 255 5.4.3 MAINTAIN A WRITTEN ASSUMPTIONS DOCUMENT AND
PERFORM A STRUCTURED WALK-THROUGH 255 5.4.4 VALIDATE COMPONENTS OF THE
MODEL BY USING QUANTITATIVE TECHNIQUES 257 X CONTENTS 5.4.5 VALIDATE THE
OUTPUT FROM THE OVERALL SIMULATION MODEL 259 5.4.6 ANIMATION 264 5.5
MANAGEMENT S ROLE IN THE SIMULATION PROCESS 264 5.6 STATISTICAL
PROCEDURES FOR COMPARING REAL-WORLD OBSERVATIONS AND SIMULATION OUTPUT
DATA 265 5.6.1 INSPECTION APPROACH 265 5.6.2 CONFIDENCE-INTERVAL
APPROACH BASED ON INDEPENDENT DATA 269 5.6.3 TIME-SERIES APPROACHES 272
5.6.4 OTHER APPROACHES 272 PROBLEMS 273 CHAPTER 6 SELECTING INPUT
PROBABILITY DISTRIBUTIONS 275 6.1 INTRODUCTION 275 6.2 USEFUL
PROBABILITY DISTRIBUTIONS 281 6.2.1 PARAMETERIZATION OF CONTINUOUS
DISTRIBUTIONS 281 6.2.2 CONTINUOUS DISTRIBUTIONS 282 6.2.3 DISCRETE
DISTRIBUTIONS 301 6.2.4 EMPIRICAL DISTRIBUTIONS 301 6.3 TECHNIQUES FOR
ASSESSING SAMPLE INDEPENDENCE 312 6.4 ACTIVITY I: HYPOTHESIZING FAMILIES
OF DISTRIBUTIONS 315 6.4.1 SUMMARY STATISTICS 316 6.4.2 HISTOGRAMS 318
6.4.3 QUANTILE SUMMARIES AND BOX PLOTS 320 6.5 ACTIVITY II: ESTIMATION
OF PARAMETERS 326 6.6 ACTIVITY III: DETERMINING HOW REPRESENTATIVE THE
FITTED DISTRIBUTIONS ARE 330 6.6.1 HEURISTIC PROCEDURES 330 6.6.2
GOODNESS-OF-FIT TESTS 340 6.7 THE EXPERTFIT SOFTWARE AND AN EXTENDED
EXAMPLE 353 6.8 SHIFTED AND TRUNCATED DISTRIBUTIONS 359 6.9 BEZIER
DISTRIBUTIONS 361 6.10 SPECIFYING MULTIVARIATE DISTRIBUTIONS,
CORRELATIONS, AND STOCHASTIC PROCESSES 362 6.10.1 SPECIFYING
MULTIVARIATE DISTRIBUTIONS 363 6.10.2 SPECIFYING ARBITRARY MARGINAL
DISTRIBUTIONS AND CORRELATIONS 366 6.10.3 SPECIFYING STOCHASTIC
PROCESSES 367 6.11 SELECTING A DISTRIBUTION IN THE ABSENCE OF DATA 370
6.12 MODELS OFARRIVAL PROCESSES 375 6.12.1 POISSON PROCESSES 375 6.12.2
NONSTATIONARY POISSON PROCESSES 377 6.12.3 BATCHARRIVALS 379 CONTENTS XI
6.13 ASSESSING THE HOMOGENEITY OF DIFFERENT DATA SETS 380 APPENDIX 6A:
TABLES OF MLES FOR THE GAMMA AND BETA DISTRIBUTIONS 381 PROBLEMS 384
CHAPTER 7 RANDOM-NUMBER GENERATORS 389 7.1 INTRODUCTION 389 7.2 LINEAR
CONGRUENTIAL GENERATORS 393 7.2.1 MIXED GENERATORS 395 7.2.2
MULTIPLICATIVE GENERATORS 396 7.3 OTHER KINDS OF GENERATORS 398 7.3.1
MORE GENERAL CONGRUENCES 398 7.3.2 COMPOSITE GENERATORS 399 7.3.3
FEEDBACK SHIFT REGISTER GENERATORS 401 7.4 TESTING RANDOM-NUMBER
GENERATORS 405 7.4.1 EMPIRICAL TESTS 406 7.4.2 THEORETICAL TESTS 410
7.4.3 SOME GENERAL OBSERVATIONS ON TESTING 414 APPENDIX 7A: PORTABLE C
CODE FOR A PMMLCG 415 APPENDIX 7B: PORTABLE C CODE FOR A COMBINED MRG
417 PROBLEMS 419 CHAPTER 8 GENERATING RANDOM VARIATES 422 8.1
INTRODUCTION 422 8.2 GENERAL APPROACHES TO GENERATING RANDOM VARIATES
424 8.2.1 INVERSE TRANSFORM 424 8.2.2 COMPOSITION 433 8.2.3 CONVOLUTION
436 8.2.4 ACCEPTANCE-REJECTION 437 8.2.5 RATIO OFUNIFORMS 444 8.2.6
SPECIAL PROPERTIES 446 8.3 GENERATING CONTINUOUS RANDOM VARIATES 447
8.3.1 UNIFORM 448 8.3.2 EXPONENTIAL 448 8.3.3 RA-ERLANG 449 8.3.4 GAMMA
449 8.3.5 WEIBULL 452 8.3.6 NORMAL 453 8.3.7 LOGNORMAL 454 8.3.8 BETA
455 8.3.9 PEARSON TYPE V 456 8.3.10 PEARSON TYPE VI 456 8.3.11
LOG-LOGISTIC 456 XLL CONTENTS 8.3.12 JOHNSON BOUNDED 456 8.3.13 JOHNSON
UNBOUNDED 457 8.3.14 BEZIER 457 8.3.15 TRIANGULAER 457 8.3.16 EMPIRICAL
DISTRIBUTIONS 45 8 8.4 GENERATING DISCRETE RANDOM VARIATES 459 8.4.1
BERNOULLI 460 8.4.2 DISCRETE UNIFORM 460 8.4.3 ARBITRARY DISCRETE
DISTRIBUTION 460 8.4.4 BINOMIAL 465 8.4.5 GEOMETRIE 465 8.4.6 NEGATIVE
BINOMIAL 465 8.4.7 POISSON 466 8.5 GENERATING RANDOM VECTORS, CORRELATED
RANDOM VARIATES, AND STOCHASTIC PROCESSES 466 8.5.1 USING CONDITIONAL
DISTRIBUTIONS 467 8.5.2 MULTIVARIATE NORMAL AND MULTIVARIATE LOGNORMAL
468 8.5.3 CORRELATED GAMMA RANDOM VARIATES 469 8.5.4 GENERATING FROM
MULTIVARIATE FAMILIES 470 8.5.5 GENERATING RANDOM VECTORS WITH
ARBITRARILY SPECIFIED MARGINAL DISTRIBUTIONS AND CORRELATIONS 470 8.5.6
GENERATING STOCHASTIC PROCESSES 471 8.6 GENERATING ARRIVAL PROCESSES 472
8.6.1 POISSON PROCESSES 473 8.6.2 NONSTATIONARY POISSON PROCESSES 473
8.6.3 BATCHARRIVALS 477 APPENDIX 8A: VALIDITY OF THE
ACCEPTANCE-REJECTION METHOD 477 APPENDIX 8B: SETUP FOR THE ALIAS METHOD
478 PROBLEMS 479 CHAPTER 9 OUTPUT DATA ANALYSIS FOR A SINGLE SYSTEM 485
9.1 INTRODUCTION 485 9.2 TRANSIENT AND STEADY-STATE BEHAVIOR OF A
STOCHASTIC PROCESS 488 9.3 TYPES OF SIMULATIONS WITH REGARD TO OUTPUT
ANALYSIS 490 9.4 STATISTICAL ANALYSIS FOR TERMINATING SIMULATIONS 494
9.4.1 ESTIMATING MEANS 495 9.4.2 ESTIMATING OTHER MEASURES OF
PERFORMANCE 504 9.4.3 CHOOSING INITIAL CONDITIONS 507 9.5 STATISTICAL
ANALYSIS FOR STEADY-STATE PARAMETERS 508 9.5.1 THE PROBLEM OF THE
INITIAL TRANSIENT 508 9.5.2 REPLICATION/DELETION APPROACH FOR MEANS 517
9.5.3 OTHER APPROACHES FOR MEANS 519 9.5.4 ESTIMATING OTHER MEASURES OF
PERFORMANCE 533 CONTENTS XLLL 9.6 STATISTICAL ANALYSIS FOR STEADY-STATE
CYCLE PARAMETERS 534 9.7 MULTIPLE MEASURES OF PERFORMANCE 537 9.8 TIME
PLOTS OF IMPORTANT VARIABLES 540 APPENDIX 9A: RATIOS OF EXPECTATIONS AND
JACKKNIFE ESTIMATORS 542 PROBLEMS 543 CHAPTER 10 COMPARING ALTERNATIVE
SYSTEM CONNGURATIONS 548 10.1 INTRODUCTION 548 10.2 CONFIDENCE INTERVALS
FOR THE DIFFERENCE BETWEEN THE EXPECTED RESPONSES OF TWO SYSTEMS 552
10.2.1 APAIRED-F CONFIDENCE INTERVAL 552 10.2.2 A MODIFIED TWO-SAMPLE-F
CONFIDENCE INTERVAL 554 10.2.3 CONTRASTING THE TWO METHODS 555 10.2.4
COMPARISONS BASED ON STEADY-STATE MEASURES OF PERFORMANCE 555 10.3
CONFIDENCE INTERVALS FOR COMPARING MORE THAN TWO SYSTEMS 557 10.3.1
COMPARISONS WITH A STANDARD 558 10.3.2 ALL PAIRWISE COMPARISONS 560
10.3.3 MULTIPLE COMPARISONS WITH THE BEST 561 10.4 RANKING AND SELECTION
561 10.4.1 SELECTING THE BEST OF K SYSTEMS 562 10.4.2 SELECTING A SUBSET
OF SIZE M CONTAINING THE BEST OF K SYSTEMS 568 10.4.3 ADDITIONAL
PROBLEMS AND METHODS 569 APPENDIX 10A: VALIDITY OF THE SELECTION
PROCEDURES 572 APPENDIX 10B: CONSTANTS FOR THE SELECTION PROCEDURES 573
PROBLEMS 575 CHAPTER 11 VARIANCE-REDUCTION TECHNIQUES 577 11.1
INTRODUCTION 577 11.2 COMMON RANDOM NUMBERS 578 11.2.1 RATIONALE 579
11.2.2 APPLICABILITY 580 11.2.3 SYNCHRONIZATION 582 11.2.4 SOMEEXAMPLES
586 11.3 ANTITHETIC VARIATES 594 11.4 CONTROL VARIATES 600 11.5 INDIRECT
ESTIMATION 607 11.6 CONDITIONING 609 PROBLEMS 613 XIV CONTENTS CHAPTER
12 EXPERIMENTAL DESIGN AND OPTIMIZATION 619 12.1 INTRODUCTION 619 12.2
2* FACTORIAL DESIGNS 622 12.3. 2 K ~ P FRACTIONAL FACTORIAL DESIGNS 636
12.4 RESPONSE SURFACES AND METAMODELS 643 12.5 SIMULATION-BASED
OPTIMIZATION 655 12.5.1 OPTIMUM-SEEKING METHODS 657 12.5.2
OPTIMUM-SEEKING PACKAGES INTERFACED WITH SIMULATION SOFTWARE 658
PROBLEMS 666 CHAPTER 13 SIMULATION OF MANUFACTURING SYSTEMS 669 13.1
INTRODUCTION 669 13.2 OBJECTIVES OF SIMULATION IN MANUFACTURING 670 13.3
SIMULATION SOFTWARE FOR MANUFACTURING APPLICATIONS 672 13.3.1 FLEXSIM
672 13.3.2 PROMODEL 675 13.3.3 OTHER MANUFACTURING-ORIENTED SIMULATION
PACKAGES 684 13.4 MODELING SYSTEM RANDOMNESS 685 13.4.1 SOURCES OF
RANDOMNESS 685 13.4.2 MACHINE DOWNTIMES 687 13.5 AN EXTENDED EXAMPLE 694
13.5.1 PROBLEM DESCRIPTION AND SIMULATION RESULTS 694 13.5.2 STATISTICAL
CALCULATIONS 703 13.6 A SIMULATION CASE STUDY OF A METAL-PARTS
MANUFACTURING FACILITY 704 13.6.1 DESCRIPTION OF THE SYSTEM 705 13.6.2
OVERALL OBJECTIVES AND ISSUES TO BE INVESTIGATED 705 13.6.3 DEVELOPMENT
OF THE MODEL 706 13.6.4 MODEL VERIFICATION AND VALIDATION 707 13.6.5
RESULTS OF THE SIMULATION EXPERIMENTS 708 13.6.6 CONCLUSIONS AND
BENEFITS 711 PROBLEMS 712 APPENDIX 715 REFERENCES 719 SUBJECT INDEX 751
|
| adam_txt |
SIMULATION MODELING AND ANALYSIS ' * : . '. *K^'I'-S*.';'*/,.ISR ;
:^-W'*.»V". I'-I.-,'.--; I -.*.*. * .'.;** !;**.**; .".,.':,S :
.Y.--,:',.-:.V: : FOURTH EDITION AVERILL M. LAW PRESIDENT AVERILL M.
LAW & ASSOCIATES, INC. TUCSON, ARIZONA, USA WWW.AVERILL-LAW.COM BOSTON
BURR RIDGE, IL DUBUQUE, IA MADISON, WL NEW YORK SAN FRANCISCO ST. LOUIS
BANGKOK BOGOTA CARACAS KUALA LUMPUR LISBON LONDON MADRID MEXICO CITY
MILAN MONTREAL NEW DELHI SANTIAGO SEOUL SINGAPORE SYDNEY TAIPEI TORONTO
CONTENTS LIST OF SYMBOLS XV PREFACE XVII 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 C 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 C
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 1.7 STEPS IN A SOUND SIMULATION STUDY 66 1.8 OTHER TYPES
OF SIMULATION 70 1.8.1 CONTINUOUS SIMULATION 70 1.8.2 COMBINED
DISCRETE-CONTINUOUS SIMULATION 72 1.8.3 MONTE CARLO SIMULATION 73 1.8.4
SPREADSHEET SIMULATION 74 VLL VLLL CONTENTS 1.9 ADVANTAGES,
DISADVANTAGES, AND PITFALLS OF SIMULATION 76 APPENDIX 1A:
FIXED-INCREMENT TIME ADVANCE 78 APPENDIX 1B: A PRIMER ON QUEUEING
SYSTEMS 79 1B.1 COMPONENTS OF A QUEUEING SYSTEM 80 IB.2 NOTATION FOR
QUEUEING SYSTEMS 80 IB.3 MEASURES OF PERFORMANCE FOR QUEUEING SYSTEMS 81
PROBLEMS 84 CHAPTER 2 MODELING COMPLEX SYSTEMS 91 2.1 INTRODUCTION 91
2.2 LIST PROCESSING IN SIMULATION 92 2.2.1 APPROACHES TO STORING LISTS
IN A COMPUTER 92 2.2.2 LINKED STORAGE ALLOCATION 93 2.3 A SIMPLE
SIMULATION LANGUAGE: SIMLIB 99 2.4 SINGLE-SERVER QUEUEING SIMULATION
WITH SIMLIB 108 2.4.1 PROBLEM STATEMENT 108 2.4.2 SIMLIB PROGRAM 108
2.4.3 SIMULATION OUTPUT AND DISCUSSION 113 2.5 TIME-SHARED COMPUTER
MODEL 114 2.5.1 PROBLEM STATEMENT 114 2.5.2 SIMLIB PROGRAM 115 2.5.3
SIMULATION OUTPUT AND DISCUSSION 123 2.6 MULTITELLER BANK WITH JOCKEYING
126 2.6.1 PROBLEM STATEMENT 126 2.6.2 SIMLIB PROGRAM 127 2.6.3
SIMULATION OUTPUT AND DISCUSSION 137 2.7 JOB-SHOP MODEL 140 2.7.1
PROBLEM STATEMENT 140 2.7.2 SIMLIB PROGRAM 142 2.7.3 SIMULATION OUTPUT
AND DISCUSSION 153 2.8 EFFICIENT EVENT-LIST MANIPULATION 155 APPENDIX
2A: C CODE FOR SIMLIB 156 PROBLEMS 169 CHAPTER 3 SIMULATION SOFTWARE 187
3.1 INTRODUCTION 187 3.2 COMPARISON OF SIMULATION PACKAGES WITH
PROGRAMMING LANGUAGES 188 3.3 CLASSIFICATION OF SIMULATION SOFTWARE 189
3.3.1 GENERAL-PURPOSE VS. APPLICATION-ORIENTED SIMULATION PACKAGES 189
CONTENTS IX 3.3.2 MODELING APPROACHES 190 3.3.3 COMMON MODELING ELEMENTS
192 3.4 DESIRABLE SOFTWARE FEATURES 193 3.4.1 GENERAL CAPABILITIES 193
3.4.2 HARDWARE AND SOFTWARE REQUIREMENTS 195 3.4.3 ANIMATION AND DYNAMIC
GRAPHICS 195 3.4.4 STATISTICAL CAPABILITIES 197 3.4.5 CUSTOMER SUPPORT
AND DOCUMENTATION 198 3.4.6 OUTPUT REPORTS AND GRAPHICS 199 3.5
GENERAL-PURPOSE SIMULATION PACKAGES 200 3.5.1 ARENA 200 3.5.2 EXTEND 206
3.5.3 OTHER GENERAL-PURPOSE SIMULATION PACKAGES 211 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 228 4.5 CONFIDENCE INTERVALS AND
HYPOTHESIS TESTS FOR THE MEAN 232 4.6 THE STRONG LAW OF LARGE NUMBERS
237 4.7 THE DANGER OF REPLACING A PROBABILITY DISTRIBUTION BY ITS MEAN
238 APPENDIX 4A: COMMENTS ON COVARIANCE-STATIONARY PROCESSES 239
PROBLEMS 239 CHAPTER 5 BUILDING VALID, CREDIBLE, AND APPROPRIATELY
DETAILED SIMULATION MODELS 243 5.1 INTRODUCTION AND DEFINITIONS 243 5.2
GUIDELINES FOR DETERMINING THE LEVEL OF MODEL DETAIL 246 5.3
VERIFICATION OF SIMULATION COMPUTER PROGRAMS 248 5.4 TECHNIQUES FOR
INCREASING MODEL VALIDITY AND CREDIBILITY 253 5.4.1 COLLECT HIGH-QUALITY
INFORMATION AND DATA ON THE SYSTEM 253 5.4.2 INTERACT WITH THE MANAGER
ON A REGULAER BASIS 255 5.4.3 MAINTAIN A WRITTEN ASSUMPTIONS DOCUMENT AND
PERFORM A STRUCTURED WALK-THROUGH 255 5.4.4 VALIDATE COMPONENTS OF THE
MODEL BY USING QUANTITATIVE TECHNIQUES 257 X CONTENTS 5.4.5 VALIDATE THE
OUTPUT FROM THE OVERALL SIMULATION MODEL 259 5.4.6 ANIMATION 264 5.5
MANAGEMENT'S ROLE IN THE SIMULATION PROCESS 264 5.6 STATISTICAL
PROCEDURES FOR COMPARING REAL-WORLD OBSERVATIONS AND SIMULATION OUTPUT
DATA 265 5.6.1 INSPECTION APPROACH 265 5.6.2 CONFIDENCE-INTERVAL
APPROACH BASED ON INDEPENDENT DATA 269 5.6.3 TIME-SERIES APPROACHES 272
5.6.4 OTHER APPROACHES 272 PROBLEMS 273 CHAPTER 6 SELECTING INPUT
PROBABILITY DISTRIBUTIONS 275 6.1 INTRODUCTION 275 6.2 USEFUL
PROBABILITY DISTRIBUTIONS 281 6.2.1 PARAMETERIZATION OF CONTINUOUS
DISTRIBUTIONS 281 6.2.2 CONTINUOUS DISTRIBUTIONS 282 6.2.3 DISCRETE
DISTRIBUTIONS 301 6.2.4 EMPIRICAL DISTRIBUTIONS 301 6.3 TECHNIQUES FOR
ASSESSING SAMPLE INDEPENDENCE 312 6.4 ACTIVITY I: HYPOTHESIZING FAMILIES
OF DISTRIBUTIONS 315 6.4.1 SUMMARY STATISTICS 316 6.4.2 HISTOGRAMS 318
6.4.3 QUANTILE SUMMARIES AND BOX PLOTS 320 6.5 ACTIVITY II: ESTIMATION
OF PARAMETERS 326 6.6 ACTIVITY III: DETERMINING HOW REPRESENTATIVE THE
FITTED DISTRIBUTIONS ARE 330 6.6.1 HEURISTIC PROCEDURES 330 6.6.2
GOODNESS-OF-FIT TESTS 340 6.7 THE EXPERTFIT SOFTWARE AND AN EXTENDED
EXAMPLE 353 6.8 SHIFTED AND TRUNCATED DISTRIBUTIONS 359 6.9 BEZIER
DISTRIBUTIONS 361 6.10 SPECIFYING MULTIVARIATE DISTRIBUTIONS,
CORRELATIONS, AND STOCHASTIC PROCESSES 362 6.10.1 SPECIFYING
MULTIVARIATE DISTRIBUTIONS 363 6.10.2 SPECIFYING ARBITRARY MARGINAL
DISTRIBUTIONS AND CORRELATIONS 366 6.10.3 SPECIFYING STOCHASTIC
PROCESSES 367 6.11 SELECTING A DISTRIBUTION IN THE ABSENCE OF DATA 370
6.12 MODELS OFARRIVAL PROCESSES 375 6.12.1 POISSON PROCESSES 375 6.12.2
NONSTATIONARY POISSON PROCESSES 377 6.12.3 BATCHARRIVALS 379 CONTENTS XI
6.13 ASSESSING THE HOMOGENEITY OF DIFFERENT DATA SETS 380 APPENDIX 6A:
TABLES OF MLES FOR THE GAMMA AND BETA DISTRIBUTIONS 381 PROBLEMS 384
CHAPTER 7 RANDOM-NUMBER GENERATORS 389 7.1 INTRODUCTION 389 7.2 LINEAR
CONGRUENTIAL GENERATORS 393 7.2.1 MIXED GENERATORS 395 7.2.2
MULTIPLICATIVE GENERATORS 396 7.3 OTHER KINDS OF GENERATORS 398 7.3.1
MORE GENERAL CONGRUENCES 398 7.3.2 COMPOSITE GENERATORS 399 7.3.3
FEEDBACK SHIFT REGISTER GENERATORS 401 7.4 TESTING RANDOM-NUMBER
GENERATORS 405 7.4.1 EMPIRICAL TESTS 406 7.4.2 THEORETICAL TESTS 410
7.4.3 SOME GENERAL OBSERVATIONS ON TESTING 414 APPENDIX 7A: PORTABLE C
CODE FOR A PMMLCG 415 APPENDIX 7B: PORTABLE C CODE FOR A COMBINED MRG
417 PROBLEMS 419 CHAPTER 8 GENERATING RANDOM VARIATES 422 8.1
INTRODUCTION 422 8.2 GENERAL APPROACHES TO GENERATING RANDOM VARIATES
424 8.2.1 INVERSE TRANSFORM 424 8.2.2 COMPOSITION 433 8.2.3 CONVOLUTION
436 8.2.4 ACCEPTANCE-REJECTION 437 8.2.5 RATIO OFUNIFORMS 444 8.2.6
SPECIAL PROPERTIES 446 8.3 GENERATING CONTINUOUS RANDOM VARIATES 447
8.3.1 UNIFORM 448 8.3.2 EXPONENTIAL 448 8.3.3 RA-ERLANG 449 "8.3.4 GAMMA
449 8.3.5 WEIBULL 452 8.3.6 NORMAL 453 8.3.7 LOGNORMAL 454 8.3.8 BETA
455 8.3.9 PEARSON TYPE V 456 8.3.10 PEARSON TYPE VI 456 8.3.11
LOG-LOGISTIC 456 XLL CONTENTS 8.3.12 JOHNSON BOUNDED 456 8.3.13 JOHNSON
UNBOUNDED 457 8.3.14 BEZIER 457 8.3.15 TRIANGULAER 457 8.3.16 EMPIRICAL
DISTRIBUTIONS 45 8 8.4 GENERATING DISCRETE RANDOM VARIATES 459 8.4.1
BERNOULLI 460 8.4.2 DISCRETE UNIFORM 460 8.4.3 ARBITRARY DISCRETE
DISTRIBUTION 460 8.4.4 BINOMIAL 465 8.4.5 GEOMETRIE 465 8.4.6 NEGATIVE
BINOMIAL 465 8.4.7 POISSON 466 8.5 GENERATING RANDOM VECTORS, CORRELATED
RANDOM VARIATES, AND STOCHASTIC PROCESSES 466 8.5.1 USING CONDITIONAL
DISTRIBUTIONS 467 8.5.2 MULTIVARIATE NORMAL AND MULTIVARIATE LOGNORMAL
468 8.5.3 CORRELATED GAMMA RANDOM VARIATES 469 8.5.4 GENERATING FROM
MULTIVARIATE FAMILIES 470 8.5.5 GENERATING RANDOM VECTORS WITH
ARBITRARILY SPECIFIED MARGINAL DISTRIBUTIONS AND CORRELATIONS 470 8.5.6
GENERATING STOCHASTIC PROCESSES 471 8.6 GENERATING ARRIVAL PROCESSES 472
8.6.1 POISSON PROCESSES 473 8.6.2 NONSTATIONARY POISSON PROCESSES 473
8.6.3 BATCHARRIVALS 477 APPENDIX 8A: VALIDITY OF THE
ACCEPTANCE-REJECTION METHOD 477 APPENDIX 8B: SETUP FOR THE ALIAS METHOD
478 PROBLEMS 479 CHAPTER 9 OUTPUT DATA ANALYSIS FOR A SINGLE SYSTEM 485
9.1 INTRODUCTION 485 9.2 TRANSIENT AND STEADY-STATE BEHAVIOR OF A
STOCHASTIC PROCESS 488 9.3 TYPES OF SIMULATIONS WITH REGARD TO OUTPUT
ANALYSIS 490 9.4 STATISTICAL ANALYSIS FOR TERMINATING SIMULATIONS 494
9.4.1 ESTIMATING MEANS 495 9.4.2 ESTIMATING OTHER MEASURES OF
PERFORMANCE 504 9.4.3 CHOOSING INITIAL CONDITIONS 507 9.5 STATISTICAL
ANALYSIS FOR STEADY-STATE PARAMETERS 508 9.5.1 THE PROBLEM OF THE
INITIAL TRANSIENT 508 9.5.2 REPLICATION/DELETION APPROACH FOR MEANS 517
9.5.3 OTHER APPROACHES FOR MEANS 519 9.5.4 ESTIMATING OTHER MEASURES OF
PERFORMANCE 533 CONTENTS XLLL 9.6 STATISTICAL ANALYSIS FOR STEADY-STATE
CYCLE PARAMETERS 534 9.7 MULTIPLE MEASURES OF PERFORMANCE 537 9.8 TIME
PLOTS OF IMPORTANT VARIABLES 540 APPENDIX 9A: RATIOS OF EXPECTATIONS AND
JACKKNIFE ESTIMATORS 542 PROBLEMS 543 CHAPTER 10 COMPARING ALTERNATIVE
SYSTEM CONNGURATIONS 548 10.1 INTRODUCTION 548 10.2 CONFIDENCE INTERVALS
FOR THE DIFFERENCE BETWEEN THE EXPECTED RESPONSES OF TWO SYSTEMS 552
10.2.1 APAIRED-F CONFIDENCE INTERVAL 552 10.2.2 A MODIFIED TWO-SAMPLE-F
CONFIDENCE INTERVAL 554 10.2.3 CONTRASTING THE TWO METHODS 555 10.2.4
COMPARISONS BASED ON STEADY-STATE MEASURES OF PERFORMANCE 555 10.3
CONFIDENCE INTERVALS FOR COMPARING MORE THAN TWO SYSTEMS 557 10.3.1
COMPARISONS WITH A STANDARD 558 10.3.2 ALL PAIRWISE COMPARISONS 560
10.3.3 MULTIPLE COMPARISONS WITH THE BEST 561 10.4 RANKING AND SELECTION
561 10.4.1 SELECTING THE BEST OF K SYSTEMS 562 10.4.2 SELECTING A SUBSET
OF SIZE M CONTAINING THE BEST OF K SYSTEMS 568 10.4.3 ADDITIONAL
PROBLEMS AND METHODS 569 APPENDIX 10A: VALIDITY OF THE SELECTION
PROCEDURES 572 APPENDIX 10B: CONSTANTS FOR THE SELECTION PROCEDURES 573
PROBLEMS 575 CHAPTER 11 VARIANCE-REDUCTION TECHNIQUES 577 11.1
INTRODUCTION 577 11.2 COMMON RANDOM NUMBERS 578 11.2.1 RATIONALE 579
11.2.2 APPLICABILITY 580 11.2.3 SYNCHRONIZATION 582 11.2.4 SOMEEXAMPLES
586 11.3 ANTITHETIC VARIATES 594 11.4 CONTROL VARIATES 600 11.5 INDIRECT
ESTIMATION 607 11.6 CONDITIONING 609 PROBLEMS 613 XIV CONTENTS CHAPTER
12 EXPERIMENTAL DESIGN AND OPTIMIZATION 619 12.1 INTRODUCTION 619 12.2
2* FACTORIAL DESIGNS 622 12.3. 2 K ~ P FRACTIONAL FACTORIAL DESIGNS 636
12.4 RESPONSE SURFACES AND METAMODELS 643 12.5 SIMULATION-BASED
OPTIMIZATION 655 12.5.1 OPTIMUM-SEEKING METHODS 657 12.5.2
OPTIMUM-SEEKING PACKAGES INTERFACED WITH SIMULATION SOFTWARE 658
PROBLEMS 666 CHAPTER 13 SIMULATION OF MANUFACTURING SYSTEMS 669 13.1
INTRODUCTION 669 13.2 OBJECTIVES OF SIMULATION IN MANUFACTURING 670 13.3
SIMULATION SOFTWARE FOR MANUFACTURING APPLICATIONS 672 13.3.1 FLEXSIM
672 13.3.2 PROMODEL 675 13.3.3 OTHER MANUFACTURING-ORIENTED SIMULATION
PACKAGES 684 13.4 MODELING SYSTEM RANDOMNESS 685 13.4.1 SOURCES OF
RANDOMNESS 685 13.4.2 MACHINE DOWNTIMES 687 13.5 AN EXTENDED EXAMPLE 694
13.5.1 PROBLEM DESCRIPTION AND SIMULATION RESULTS 694 13.5.2 STATISTICAL
CALCULATIONS 703 13.6 A SIMULATION CASE STUDY OF A METAL-PARTS
MANUFACTURING FACILITY 704 13.6.1 DESCRIPTION OF THE SYSTEM 705 13.6.2
OVERALL OBJECTIVES AND ISSUES TO BE INVESTIGATED 705 13.6.3 DEVELOPMENT
OF THE MODEL 706 13.6.4 MODEL VERIFICATION AND VALIDATION 707 13.6.5
RESULTS OF THE SIMULATION EXPERIMENTS 708 13.6.6 CONCLUSIONS AND
BENEFITS 711 PROBLEMS 712 APPENDIX 715 REFERENCES 719 SUBJECT INDEX 751 |
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| discipline_str_mv | Informatik Wirtschaftswissenschaften |
| edition | 4. ed., internat. ed. |
| format | Book |
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| id | DE-604.BV023029963 |
| illustrated | Illustrated |
| index_date | 2024-07-02T19:16:35Z |
| indexdate | 2024-07-09T21:09:22Z |
| institution | BVB |
| isbn | 9780071255196 0071255192 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016233864 |
| oclc_num | 255955662 |
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| owner | DE-92 DE-29T DE-523 DE-634 DE-11 DE-188 |
| owner_facet | DE-92 DE-29T DE-523 DE-634 DE-11 DE-188 |
| physical | XIX, 768 S. Ill., graph. Darst. 1 CD-ROM (12 cm) |
| publishDate | 2007 |
| publishDateSearch | 2007 |
| publishDateSort | 2007 |
| publisher | McGraw Hill |
| record_format | marc |
| series2 | McGraw-Hill series in industrial engineering and management science |
| spelling | Law, Averill M. Verfasser (DE-588)170238075 aut Simulation modeling and analysis Averill M. Law 4. ed., internat. ed. Boston [u.a.] McGraw Hill 2007 XIX, 768 S. Ill., graph. Darst. 1 CD-ROM (12 cm) txt rdacontent n rdamedia nc rdacarrier McGraw-Hill series in industrial engineering and management science Computersimulation - Lehrbuch Computersimulation - Stochastik - Lehrbuch Digital computer simulation Computersimulation (DE-588)4148259-1 gnd rswk-swf Computersimulation (DE-588)4148259-1 s DE-604 GBV Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016233864&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Law, Averill M. Simulation modeling and analysis Computersimulation - Lehrbuch Computersimulation - Stochastik - Lehrbuch 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_exact_search_txtP | 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 | Computersimulation - Lehrbuch Computersimulation - Stochastik - Lehrbuch Digital computer simulation Computersimulation (DE-588)4148259-1 gnd |
| topic_facet | Computersimulation - Lehrbuch Computersimulation - Stochastik - Lehrbuch Digital computer simulation Computersimulation |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016233864&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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