Computer simulation in management science:
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Chichester
Wiley
2004
|
| Edition: | 5. ed. |
| Subjects: | |
| Online Access: | Table of contents Inhaltsverzeichnis |
| Item Description: | Includes bibliographical references and index |
| Physical Description: | XVI, 311 S. graph. Darst. |
| ISBN: | 0470092300 |
Staff View
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| 100 | 1 | |a Pidd, Michael |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Computer simulation in management science |c Michael Pidd |
| 250 | |a 5. ed. | ||
| 264 | 1 | |a Chichester |b Wiley |c 2004 | |
| 300 | |a XVI, 311 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
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| 500 | |a Includes bibliographical references and index | ||
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| 650 | 7 | |a Computersimulaties |2 gtt | |
| 650 | 7 | |a Discrete gebeurtenissen |2 gtt | |
| 650 | 4 | |a Sciences de la gestion - Informatique | |
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| 650 | 4 | |a Sciences de la gestion - Simulation par ordinateur | |
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| adam_text | Contents
Preface to the Fifth Edition xv
PART I: FUNDAMENTALS OF COMPUTER SIMULATION IN
MANAGEMENT SCIENCE 1
1 The computer simulation approach 3
1.1 Models, experiments and computers 3
1.2 Some applications of computer simulation 4
1.2.1 Manufacturing 4
1.2.2 Healthcare 5
1.2.3 Business process re engineering 5
1.2.4 Transport systems ft
1.2.5 Defence 7
1.3 Models in management science 7
1.4 Simulation as experimentation 8
1.5 Why simulate? 9
1.5.1 Simulation versus direct experimentation 9
1.5.2 Simulation versus mathematical modelling 10
1.6 Summary 10
Exercises 1 1
References 1 1
2 A variety of modelling approaches 15
2.1 General considerations 15
2.2 Time handling 15
2.2.1 Time slicing 15
2.2.2 Next event technique 17
2.2.3 Time slicing or next event? 18
2.3 Stochastic or deterministic? 18
2.3.1 Deterministic simulation: a time slicing example 19
2.3.2 Stochastic simulation 21
2.4 Discrete or continuous change 25
2.4.1 Discrete change 26
2.4.2 Continuous change 26
2.4.3 A few words on simulation software 27
Exercises 2 7
References 28
3 Computer simulation in practice 29
3.1 Process, content, problem and proj ect 29
3.1.1 Process and content 2 9
3.1.2 Problems and proj ects 3 0
3.1.3 Two parallel streams 3 0
3.2 The simulation problem part of the study 32
3.3 Problem structuring 32
3.3.1 Problem structuring as exploration 3 3
3.4 Modelling 35
3.4.1 Conceptual model building 3 5
3.4.2 Computer implementation 36
3.4.3 Validation 37
3.4.4 Experimentation 38
3.4.5 Implementation 39
3.5 The project part of the study 40
3.5.1 Initial negotiation and proj ect definition 41
3.5.2 Project management and control 42
3.5.3 Project completion 43
Exercises 43
References 44
4 Static Monte Carlo simulation 45
4.1 Basic ideas 45
4.1.1 Risk and uncertainty 45
4.1.2 The replacement problem: a reprise 46
4.1.3 Static Monte Carlo simulation defined 4 7
4.2 Some important considerations 49
4.2.1 Subjective probabilities 49
4.2.2 Repeatability 50
4.3 Some simple static simulations 51
4.3.1 The loan repayment 51
4.3.2 An investment decision 5 3
4.4 Simulation on spreadsheets 57
Exercises 58
References 59
PART II: DISCRETE EVENT SIMULATION 61
5 Discrete event modelling 63
5.1 Fundamentals 63
5.2 Terminology 63
5.2.1 Objects of the system 64
5.2.2 The organization of entities 6 5
5.2.3 Operations of the entities 65
5.3 Activity cycle diagrams 66
5.3.1 Example 1: a simple j ob shop 68
5.3.2 Example 2: the harassed booking clerk 71
5.3.3 Example 3: the delivery depot 74
5.3.4 Using the activity cycle diagram 7 7
5.4 Activity cycle diagrams: a caveat 78
Exercises 79
References 81
6 How discrete simulation software works 8 3
6.1 Introduction 83
6.1.1 Why understand how simulation software is
organized? 8 3
6.1.2 Simulation executives in more detail 84
6.1.3 Application logic 85
6.2 The three phase approach 85
6.2.1 Bs 85
6.2.2 Cs 86
6.2.3 The exception to the general rule 8 7
6.2.4 Bs and Cs in the harassed booking clerk problem 88
6.2.5 Another example: a T junction 89
6.3 How the three phase approach works 90
6.3.1 The A phase 92
6.3.2 The B phase 92
6.3.3 The C phase 92
6.4 The harassed booking clerk—a manual three phase
simulation 9 5
6.4.1 The first A phase 94
6.4.2 The first B phase 94
6.4.3 The first C phase 95
6.4.4 The second A phase 95
6.4.5 The next B and C phases 96
6.4.6 The third A phase 96
6.4.7 The third B phase 96
6.5 The event based worldview 97
6.5.1 Events in the harassed booking clerk problem 9 7
6.5.2 Event based executives 99
6.6 The activity scanning approach 100
6.6.1 Activities 100
6.6.2 Activity scanning executives 101
6.7 Process based approaches 101
6.7.1 Processes in the harassed booking clerk problem 102
6.7.2 Process interaction 103
6.7.3 Process based executives 104
6.8 Which approach is best? 105
6.8.1 Three phase versus process based approaches 105
Exercises 106
References 108
7 Writing a three phase simulation program 109
7.1 Introduction 109
7.1.1 The basic structure of the library 110
7.2 Inside the executive 111
7.2.1 The control array 112
7.2.2 Using the control array to operate a three phase
simulation 11 2
7.3 The Visual Basic implementation 113
7.3.1 Some comments on Visual Basic 113
7.3.2 The variables and their types 114
7.3.3 The A phase 116
7.3.4 The B phase 118
7.3.5 TheCphase 119
7.3.6 Running the simulation 119
7.4 Using VBSim to simulate the harassed booking clerk problem 120
7.4.1 Entities, Bs and Cs 120
7.4.2 Personal enquirers and phone calls arrive 121
7.4.3 The end of personal service and phone calls 123
7.4.4 Observations 124
7.4.5 TheCs 124
7.4.6 Initialization and finalization 125
7.5 Putting it all together 126
Exercises 127
References 128
8 Visual interactive modelling and simulation 129
8.1 Basic ideas 129
8.1.1 Visual interactive modelling (VIM) 129
8.1.2 Visual simulation output 130
8.1.3 Interaction 131
8.1.4 A caveat 132
8.2 Designing a visual simulation display 132
8.2.1 Iconic displays 133
8.2.2 Logical displays 134
8.2.3 Chart displays 135
8.3 VIMS 136
8.3.1 Joe s exhaust parlour 136
8.3.2 Joe s exhaust parlour in Micro Saint: model building 138
8.3.3 Joe s exhaust parlour in Micro Saint: running and
analysing the simulation 140
8.3.4 Joe s exhaust parlour in SIMUL8: model building 143
8.3.5 Joe s exhaust parlour in SIMUL8: running and
analysing the simulation 14 5
8.4 Visual interactive simulation: a reprise 146
Exercises 146
References 146
9 Discrete simulation software 149
9.1 General principals 149
9.2 A quick overview of discrete simulation software 150
9.3 VIMS and their relatives 151
9.3.1 VIMS—a reprise 151
9.3.2 Block diagram systems 152
9.3.3 VIMS and block diagram systems 157
9.4 Programming using a general purpose language 158
9.4.1 Pros and cons 158
9.4.2 Libraries and component based software 159
9.5 Programming approaches using simulation languages 161
9.5.1 Common features of simulation languages 162
9.5.2 Anexample:SIMSCRIPTII.5 163
9.6 Layered systems and application templates 168
9.6.1 Layered systems 168
9.6.2 Application templates 169
9.7 Appraising simulation software: some principles 169
9.7.1 The type of application 170
9.7.2 The expectations for end use 170
9.7.3 Knowledge, computing policy and user support 171
9.7.4 Price 171
9.8 Which to choose? Horses for courses 172
9.8.1 VIMS 172
9.8.2 Simulation languages 172
References 1 7 3
10 Sampling methods 175
10.1 Basic ideas 175
10.1.1 General principles of random sampling ] 76
10.1.2 Top hat sampling 177
10.1.3 The fundamental random sampling process 178
10.1.4 Use of pre written libraries of algorithms 179
10.2 Random number generation 179
10.2.1 Truly random numbers 179
10.2.2 Pseudo random numbers 180
10.2.3 Congruential generators 181
10.2.4 General requirements for these generators 182
10.2.5 Multiplicative congruential generators 182
10.2.6 Improving on simple congruential generators 184
10.2.7 Using inbuilt random number generators 185
10.3 Testing random number generators 185
10.3.1 Scatter plots 186
10.3.2 Auxiliary sequences 187
10.3.3 Frequency tests 187
10.3.4 Serial test 188
10.3.5 Gap test 188
10.3.6 Other tests 188
10.4 General methods for random sampling from continuous
distributions 189
10.4.1 Inversion 189
10.4.2 Rejection 192
10.4.3 Composition 193
10.5 Random sampling algorithms for discrete distributions 193
10.5.1 Sampling from histograms 193
10.5.2 Implicit inverse transformation 194
10.5.3 Discrete rejection—samples from a Poisson
distribution 196
10.6 Sampling from the normal distribution 197
10.6.1 The original Box Miiller method 198
10.6.2 Box Miiller polar variation 199
10.6.3 Sampling from a normal distribution by composition 200
10 6 4 A Poor way to sample from the normal distribution 201
ins ving one distribution from another—log normal variates 201
10.8 Sampling from non stationary processes: thinning 202
exercises 203
References 204
11 Planning and analysing discrete simulation output 207
11.1 Fundamental ideas 207
11 1.1 Simulation as directed experimentation 207
11 1.2 Estimation and comparison 208
11 1.3 Three important principles 209
11.1.4 Some preliminary advice 210
11 2 Dealing with transient effects 210
11 2.1 Terminating and non terminating systems 210
11.2.2 Achieving steady state 212
11 2.3 Using a run in period 213
11.2.4 Welch s method for determining the run in period 214
11.3 Dealing with lack of independence 215
11.3.1 Simple replication 215
11.3.2 Using batch means 216
11.3.3 Overlapping batch means (OBM) 217
11.3.4 Regenerative methods 218
11.4 Variance reduction 218
11.4.1 The basic problem—sampling variation 219
11.4.2 Set and sequence effects 220
11.4.3 Common random number streams and
synchronization 222
11.4.4 Control variates (regression sampling) 223
11.4.5 Antithetic variates 225
11.5 Descriptive sampling 226
11.5.1 Basic idea 226
11.5.2 Procedure 227
11.6 Experimentation 228
11.6.1 Basic ideas 228
11.6.2 Factorial experiments 229
Exercises 231
References 231
12 Model Testing and Validation 23 3
12.1 The importance of validation 23 3
12.1.1 Validation is impossible, but desirable 233
12.1.2 Some practical issues 2 34
12.1.3 The real world, the model and observation 2 35
12.1.4 Thehypothetico deductive approach 2 36
12.1.5 The importance of process and other aspects 2 37
12.2 Validation and comparison 2 37
12.2.1 Experimental frames 2 38
12.2.2 Program verification and model validation 2 39
12.3 Black box validation 240
12.3.1 Blackbox validation: a model s predictive power 240
12.3.2 How valid? 240
12.3.3 Validation errors 241
12.3.4 Testing model components 241
12.4 White box validation 242
12.4.1 Detailed internal structure 242
12.4.2 Input distributions 242
12.4.3 Static logic 24 3
12.4.4 Dynamic logic 244
12.5 Type zero errors 245
12.5.1 Over elaboration 245
12.5.2 Over simplification 246
12.5.3 Steering a sensible course 246
References 246
PART III: SYSTEM DYNAMICS 247
13 Structure, behaviour, events and Feedback systems 249
13.1 Events, behaviours and structures 249
13.1.1 System simulation 249
13.1.2 The importance of system structure 250
13.2 Feedback systems 251
13.2.1 Hierarchical feedback systems: an example 251
13.2.2 Causal loop diagrams 253
13.3 Modelling feedback systems 255
13.3.1 Delays 255
13.3.2 Levels and stocks 256
13.3.3 Rates and flows 257
13.3.4 Policies 258
13.4 The origings of system dynamics 258
13.4.1 Control theory 259
Exercises 260
References 261
14 System dynamics modelling and simulation 263
14.1 Introduction 263
14.1.1 Stock and flow diagrams 264
14.1.2 A stock and flow diagram for Big Al s problem 265
14.2 Beyond the diagrams—system dynamics simulation 266
14.2.1 Time handling in system dynamics 267
14.2.2 Equation types 268
14.2.3 Powersim equations for Big Al s problem 269
14.2.4 Integration and the value of dt 270
14.3 Simulating delays in system dynamics 2 72
14.3.1 Pipeline delays 272
14.3.2 Exponential delays 272
14.3.3 Information delays 274
14.4 System dynamics modelling L
14.4.1 Modelling from the outside in 275
14.4.2 Modelling from the inside out 276
Exercises 27/
References ^
9 7Q
15 System dynamics in practice z
15.1 Associated Spares Ltd 279
7 79
15.1.1 The problem as originally posed A
15.1.2 The multi echelon system 28°
15.1.3 The retail branch model 28°
15.1.4 The regional warehouse model 2
15.1.5 The central warehouse model 284
15.1.6 The total system model 285
15.1.7 Some conclusions 286
15.1.8 Apostscript 287
15.2 DynastatLtd 288
15.2.1 An expansion programme 288
15.2.2 The manpower problem 288
15.2.3 Recruitment 288
15.2.4 Turnover 289
15.2.5 Some effects of this structure 290
15.2.6 Validating the model 290
15.2.7 Simulation results 291
15.2.8 Predicting length of service 292
15.2.9 The value of the exercise to Dynastat 292
15.3 System dynamics in practice 293
15.3.1 Simple models 293
15.3.2 Communication 294
15.3.3 New thinking 294
15.3.4 Evolutionary involvement 295
References 295
Index 297
|
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| dewey-tens | 650 - Management and auxiliary services |
| discipline | Wirtschaftswissenschaften |
| edition | 5. ed. |
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| id | DE-604.BV019307418 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T19:57:17Z |
| institution | BVB |
| isbn | 0470092300 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-012775371 |
| oclc_num | 54487381 |
| open_access_boolean | |
| owner | DE-355 DE-BY-UBR DE-573 DE-473 DE-BY-UBG DE-M347 DE-634 |
| owner_facet | DE-355 DE-BY-UBR DE-573 DE-473 DE-BY-UBG DE-M347 DE-634 |
| physical | XVI, 311 S. graph. Darst. |
| publishDate | 2004 |
| publishDateSearch | 2004 |
| publishDateSort | 2004 |
| publisher | Wiley |
| record_format | marc |
| spelling | Pidd, Michael Verfasser aut Computer simulation in management science Michael Pidd 5. ed. Chichester Wiley 2004 XVI, 311 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references and index Bedrijfskunde gtt Computersimulaties gtt Discrete gebeurtenissen gtt Sciences de la gestion - Informatique Sciences de la gestion - Modèles mathématiques Sciences de la gestion - Simulation par ordinateur Systeemdynamica gtt Management science Computer simulation Management (DE-588)4037278-9 gnd rswk-swf Computersimulation (DE-588)4148259-1 gnd rswk-swf Theorie (DE-588)4059787-8 gnd rswk-swf Operations Research (DE-588)4043586-6 gnd rswk-swf Operations Research (DE-588)4043586-6 s Computersimulation (DE-588)4148259-1 s DE-604 Management (DE-588)4037278-9 s Theorie (DE-588)4059787-8 s 1\p DE-604 http://www.loc.gov/catdir/toc/ecip0415/2004003361.html Table of contents HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=012775371&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Pidd, Michael Computer simulation in management science Bedrijfskunde gtt Computersimulaties gtt Discrete gebeurtenissen gtt Sciences de la gestion - Informatique Sciences de la gestion - Modèles mathématiques Sciences de la gestion - Simulation par ordinateur Systeemdynamica gtt Management science Computer simulation Management (DE-588)4037278-9 gnd Computersimulation (DE-588)4148259-1 gnd Theorie (DE-588)4059787-8 gnd Operations Research (DE-588)4043586-6 gnd |
| subject_GND | (DE-588)4037278-9 (DE-588)4148259-1 (DE-588)4059787-8 (DE-588)4043586-6 |
| title | Computer simulation in management science |
| title_auth | Computer simulation in management science |
| title_exact_search | Computer simulation in management science |
| title_full | Computer simulation in management science Michael Pidd |
| title_fullStr | Computer simulation in management science Michael Pidd |
| title_full_unstemmed | Computer simulation in management science Michael Pidd |
| title_short | Computer simulation in management science |
| title_sort | computer simulation in management science |
| topic | Bedrijfskunde gtt Computersimulaties gtt Discrete gebeurtenissen gtt Sciences de la gestion - Informatique Sciences de la gestion - Modèles mathématiques Sciences de la gestion - Simulation par ordinateur Systeemdynamica gtt Management science Computer simulation Management (DE-588)4037278-9 gnd Computersimulation (DE-588)4148259-1 gnd Theorie (DE-588)4059787-8 gnd Operations Research (DE-588)4043586-6 gnd |
| topic_facet | Bedrijfskunde Computersimulaties Discrete gebeurtenissen Sciences de la gestion - Informatique Sciences de la gestion - Modèles mathématiques Sciences de la gestion - Simulation par ordinateur Systeemdynamica Management science Computer simulation Management Computersimulation Theorie Operations Research |
| url | http://www.loc.gov/catdir/toc/ecip0415/2004003361.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=012775371&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT piddmichael computersimulationinmanagementscience |