Introduction to discrete event simulation and agent-based modeling: voting systems, health care, military, and manufacturing

✍ Scribed by Allen, Theodore T

• Publisher: Springer
• Year: 2011
• Tongue: English
• Leaves: 220
• Category: Library

✦ Synopsis

Discrete event simulation and agent-based modeling are increasingly recognized as critical for diagnosing and solving process issues in complex systems. Introduction to Discrete Event Simulation and Agent-based Modeling covers the techniques needed for success in all phases of simulation projects. These include: - Definition - The reader will learn how to plan a project and communicate using a charter. - Input analysis - The reader will discover how to determine defensible sample sizes for all needed data collections. They will also learn how to fit distributions to that data. - Simulation - The reader will understand how simulation controllers work, the Monte Carlo (MC) theory behind them, modern verification and validation, and ways to speed up simulation using variation reduction techniques and other methods. - Output analysis - The reader will be able to establish simultaneous intervals on key responses and apply selection and ranking, design of experiments (DOE), and black box optimization to develop defensible improvement recommendations. - Decision support - Methods to inspire creative alternatives are presented, including lean production. Also, over one hundred solved problems are provided and two full case studies, including one on voting machines that received international attention. Introduction to Discrete Event Simulation and Agent-based Modeling demonstrates how simulation can facilitate improvements on the job and in local communities. It allows readers to competently apply technology considered key in many industries and branches of government. It is suitable for undergraduate and graduate students, as well as researchers and other professionals.

✦ Table of Contents

13.2…Solutions: Chapter 2......Page 2
Index......Page 4
Foreword......Page 5
Acknowledgments......Page 6
Cover......Page 1
Introduction to Discrete Event Simulation andAgent-based Modeling......Page 3
Contents......Page 7
11.5.2 Acute-Care Facility......Page 9
11.6…Problems......Page 10
1 Introduction......Page 11
1.2…Questions about Voting Systems......Page 13
1.4…Phase 1: Define the System and Team Charter......Page 15
1.5…Problems......Page 16
13.12…Solutions: Chapter 12......Page 17
2.1…Random Variables and Expected Values......Page 18
13.9…Solutions: Chapter 9......Page 8
1.1…Domains and Uses......Page 12
1.3…Simulation Phases......Page 14
9.6…Problems......Page 19
2.2.1 Confidence Interval Construction Method......Page 21
7.6…Problems......Page 22
2.3…Expected Value Formula and Leaps of Faith......Page 24
2.4…Discrete Event Simulation......Page 26
2.4.1 Linear Congruential Generators......Page 27
2.4.2 Inverse Cumulative Distribution Functions......Page 28
2.4.3 Discrete Event Simulation......Page 30
2.5…Monte Carlo Errors......Page 32
2.6.1 Problem......Page 33
2.7…Voting Systems Example Summary......Page 34
2.8…Problems......Page 35
3.1…Guidelines for Gathering Data......Page 37
3.2.1 Relative Frequency Histograms......Page 40
3.2.2 Sum of Squares Error......Page 41
3.3.1 Constructing Cumulative Empirical Distributions......Page 43
3.3.2 The Kolmogorov--Smirnov Test......Page 44
3.4…Empirical Distributions......Page 45
3.5…Summary Example......Page 47
3.6…Problems......Page 48
4 Simulating Waiting Times......Page 51
4.1…Exponential Interarrivals or Poisson Processes......Page 52
4.2…Discrete Event Simulation Controllers......Page 53
4.3…IID Normally Distributed......Page 56
4.4.1 The Central Limit Theorem......Page 58
4.4.2 Batching for Normality......Page 59
4.5…Other Arrival Processes......Page 61
4.7…Summary Example......Page 63
4.8…Problems......Page 64
5 Output Analysis......Page 67
5.1.1 The Bonferroni Inequality and Simultaneous Intervals......Page 69
5.1.2 Which Election System Reduces Voter Waits?......Page 71
5.1.3 Sample Size Estimates......Page 73
5.2.1 Subset Selection and Indifference Zone Procedures......Page 74
5.2.2 Subset Selection......Page 75
5.2.3 An Indifference Zone Method......Page 76
5.3…Design of Experiments and Main Effects Plots (Optional)......Page 78
5.4…Black Box Simulation Optimization Methods (Optional)......Page 81
5.4.1 Variable Sample Size Methods......Page 82
5.4.2 Population Indifference Zone Search Method......Page 83
5.6…Problems......Page 84
6 Theory of Queues......Page 86
6.1…Steady State Utilization......Page 87
6.2…Number of Machines Formula......Page 88
6.3…Steady State Theory (Optional)......Page 89
6.4…Little’s Law and Expected Waiting Times......Page 91
6.6…Problems......Page 92
7 Decision Support and Voting Systems Case Study......Page 94
7.2…Lean Production......Page 95
7.3.1 Project Definition: Learning What Works......Page 97
7.3.3 Simulation and Non-Interacting Systems......Page 99
7.3.4 Output Analysis: Studying Alternative Scenarios......Page 101
7.3.5 Decision Support......Page 102
7.4.1 Problem Definition......Page 104
7.4.2 Input Analysis......Page 105
7.4.3 Simulation......Page 107
7.4.4 Modeling Using Alternative Software: SIMIO......Page 108
7.4.5 Output Analysis......Page 111
7.4.6 Decision Support......Page 112
7.5…Project Planning Exercise......Page 114
7.6…Problems......Page 115
8 Variance Reduction Techniques and Quasi-Monte Carlo......Page 118
8.1…Variance-Reduction Techniques and Common Random Numbers......Page 119
8.1.1 Common Random Numbers......Page 120
8.2.1 Latin Hypercube Sampling......Page 122
8.2.2 Descriptive Sampling......Page 123
8.2.3 Quasi-Monte Carlo Sampling......Page 124
8.2.4 Comparison of Alternative Techniques......Page 126
8.4…Getting More Out of a Stream than the Batch Average......Page 128
8.5…Problems......Page 130
9 Simulation Software and Visual Basic......Page 132
9.1…Getting Started......Page 133
9.1.1 Making a Simple Program......Page 134
9.1.2 Other Ways to Interact with Excel......Page 135
9.2…Loops: For and Do--While......Page 136
9.3…Conditional Statements: If--Then--Else and Case......Page 138
9.5…Visual Basic and Simulation......Page 139
9.5.1 Pseudorandom Numbers and Initialization......Page 140
9.5.2 The Event Controller......Page 142
9.5.3 Arrival and Departure Events......Page 144
9.5.4 Calling the Average Waiting Time Function......Page 149
9.6…Problems......Page 150
10 Introduction to ARENA Software......Page 152
10.1…Getting Started: Voting Example......Page 153
10.2…ARENA Input Analyzer......Page 160
10.3…ARENA Process Analyzer......Page 161
10.4…Processes, Resources, Queues, and Termination......Page 162
10.6…Summary Example......Page 163
10.7…Problems......Page 165
11 Advanced Modeling with ARENA......Page 168
11.1…Stations......Page 169
11.2…Animation......Page 170
11.3…Scheduling......Page 171
11.4…Manufacturing Example: Decide, Assign, and Stations......Page 172
11.5.1 Single Machine System......Page 175
11.5.2 Acute-Care Facility......Page 176
11.6…Problems......Page 177
12 Agents and New Directions......Page 182
12.1…Agent-based and Other Types of Simulation......Page 183
12.2…The History of Agent-based Simulation......Page 186
12.3…NetLogo......Page 188
12.4…New Directions......Page 193
12.5…Problems......Page 196
13.1…Solutions: Chapter 1......Page 198
13.2…Solutions: Chapter 2......Page 199
13.3…Solutions: Chapter 3......Page 200
13.4…Solutions: Chapter 4......Page 201
13.5…Solutions: Chapter 5......Page 202
13.7…Solutions: Chapter 7......Page 203
13.8…Solutions: Chapter 8......Page 204
13.9…Solutions: Chapter 9......Page 205
13.10…Solutions: Chapter 10......Page 208
13.11…Solutions: Chapter 11......Page 209
13.12…Solutions: Chapter 12......Page 214
References......Page 215
Index......Page 218