SIMULATION WITH ARENAPDF电子书下载

Chapter 1 What is Simulation？ 3

1.1 Modeling 3

1.1.1 What’s Being Modeled？ 3

1.1.2 How About Just Playing with the System？ 5

1.1.3 Sometimes You Can’t （or Shouldn’t） Play with the System 5

1.1.4 Physical Models 5

1.1.5 Logical （or Mathematical） Models 6

1.1.6 What Do You Do with a Logical Model？ 6

1.2 Computer Simulation 7

1.2.1 Popularity and Advantages 7

1.2.2 The Bad News 8

1.2.3 Different Kinds of Simulations 9

1.3 How Simulations Get Done 9

1.3.1 By Hand 10

1.3.2 Programming in General-Purpose Languages 11

1.3.3 Simulation Languages 11

1.3.4 High-Level Simulators 11

1.3.5 Where Arena Fits In 12

1.4 When Simulations Are Used 13

1.4.1 The Early Years 13

1.4.2 The Formative Years 13

1.4.3 The Recent Past 14

1.4.4 The Present 14

1.4.5 The Future 15

Chapter 2 Fundamental Simulation Concepts 19

2.1 An Example 19

2.1.1 The System 19

2.1.2 Goals of the Study 20

2.2 Analysis Options 22

2.2.1 Educated Guessing 22

2.2.2 Queueing Theory 22

2.2.3 Mechanistic Simulation 23

2.3 Pieces of a Simulation Model 24

2.3.1 Entities 24

2.3.2 Attributes 25

2.3.3 （Global） Variables 25

2.3.4 Resources 25

2.3.5 Queues 26

2.3.6 Statistical Accumulators 26

2.3.7 Events 26

2.3.8 Simulation Clock 27

2.3.9 Starting and Stopping 28

2.4 Event-Driven Hand Simulation 28

2.4.1 Outline of the Action 28

2.4.2 Keeping Track 29

2.4.3 Carrying It Out 31

2.4.4 Finishing Up 33

2.5 Event and Process-Oriented Simulation 33

2.6 Randomness in Simulation 35

2.6.1 Random Input，Random Output 35

2.6.2 Replicating the Example 35

2.6.3 Comparing Alternatives 37

2.7 Overview of a Simulation Study 38

2.8 Exercises 40

Chapter 3 A Quick Peek at Arena 43

3.1 Starting Up 43

3.2 Browsing an Existing Model 44

3.2.1 Viewing the Model Window 45

3.2.2 The Arrive Module 46

3.2.3 The Server Module 47

3.2.4 The Depart Module 49

3.2.5 The Simulate Module 49

3.2.6 Module Connections 50

3.2.7 Dynamic Plots 51

3.2.8 Dressing Things Up 52

3.2.9 Running It 53

3.3 Understanding What Just Happened 54

3.3.1 Arena’s Modeling Orientation 55

3.3.2 Launching Entities Into the Model—The Arrive Module Revisited 55

3.3.3 Processing the Entity—The Server Module Revisited 57

3.3.4 Leaving the Modeled System—The Depart Module Revisited 58

3.3.5 Controlling the Run—The Simulate Module Revisited 59

3.4 Exercises 59

Chapter 4 Working with Arena 63

4.1 Basic Interaction 63

4.2 Menus 65

4.3 Toolbars 68

4.4 Help 71

4.5 Model Windows 72

4.6 Drawing 72

4.7 Printing 74

4.8 Running 74

4.9 Building the Simple Processing Model 75

Chapter 5 Modeling Basic Operations and Inputs 85

5.1 Model 5.1：An Electronic Assembly and Test System 85

5.1.1 Developing a Modeling Approach 86

5.1.2 Some New Arena Concepts：Stations，Transfers，and Pictures 87

5.1.3 Building the Model 89

5.1.4 Running the Model 98

5.1.5 Viewing the Results 99

5.2 Model 5.2：The Enhanced Electronic Assembly and Test System 100

5.2.1 Expanding Resource Representation：Schedules and States 102

5.2.2 Resource Schedules 103

5.2.3 Resource Failures 106

5.2.4 Saving Statistical Data 107

5.2.5 Results of Model 5.2 111

5.2.6 The Output Analyzer 112

5.3 Enhancing the Animation 116

5.3.1 Changing Animation Queues 117

5.3.2 Changing Entity Pictures 119

5.3.3 Changing Resource Pictures 122

5.3.4 Adding Plots and Variables 124

5.4 Input Analysis：Specifying Model Parameters and Distributions 128

5.4.1 Deterministic vs.Random Inputs 129

5.4.2 Collecting Data 130

5.4.3 Using Data 131

5.4.4 Fitting Input Distributions via the Input Analyzer 132

5.4.5 No Data？ 139

5.4.6 Nonstationary Arrival Processes 141

5.4.7 Multivariate and Correlated Input Data 142

5.5 Summary and Forecast 142

5.6 Exercises 142

Chapter 6 Intermediate Modeling and Terminating Statistical Analysis 149

6.1 Model 6.1：A Small Manufacturing System 149

6.2 New Arena Concepts 150

6.2.1 Sequences 150

6.2.2 Variables and Expressions 152

6.2.3 Sets 153

6.3 The Modeling Approach 153

6.4 Building the Model 154

6.4.1 The Data Modules 154

6.4.2 The Logic Modules 159

6.4.3 Animation 170

6.4.4 Verification 173

6.5 Confidence Intervals for Terminating Simulations via the Output Analyzer 176

6.5.1 Time Frame of Simulations 176

6.5.2 Model 6.2：Modifying Model 6.1 for a Terminating Analysis 177

6.5.3 Strategy for Data Collection and Analysis 180

6.5.4 Confidence Intervals for Terminating Systems 182

6.5.5 Comparing Alternatives 188

6.6 Summary and Forecast 190

6.7 Exercises 190

Chapter 7 Entiry Transfer and Steady-State Statistical Analysis 197

7.1 Types of Entity Transfers 197

7.2 Resource-Constrained Transfers 199

7.3 Model 7.1：The Small Manufacturing System with Transporters 200

7.4 Conveyors 211

7.4.1 Model 7.2：The Small Manufacturing System with Nonaccumulating Conveyors 214

7.4.2 Model 7.3：The Small Manufacturing System with Accumulating Conveyors 218

7.5 Statistical Analysis of Steady-State Simulations 219

7.5.1 Warm Up and Run Length 219

7.5.2 Truncated Replications 223

7.5.3 Batching in a Single Run 224

7.5.4 Automatic Run-Time Confidence Intervals via Batch Means 232

7.5.5 What To Do？ 234

7.5.6 Other Methods and Goals for Steady-State Statistical Analysis 234

7.6 Summary and Forecast 235

7.7 Exercises 235

Chapter 8 Detailed Modeling 242

8.1 Model 8.1：A Generic Call Center System 242

8.2 New Modeling Issues 244

8.3 Terminating or Steady-State 247

8.4 Modeling Approach 247

8.5 Defining the Data 249

8.6 Determine Maximum Arrival Rate and Increment Time Period 251

8.7 Create Arrivals and Direct to Service 259

8.8 Technical Support Calls 265

8.9 Sales Calls 270

8.10 Order-Status Calls 273

8.11 Finding and Fixing Model Errors 274

8.12 Animating the Model 283

8.13 Summary and Forecast 291

8.14 Exercises 291

Chapter 9 A Sampler of Further Modeling Issues and Techniques 299

9.1 Modeling Conveyors Using the Transfer Panel 299

9.1.1 Model 9.1：Finite Buffers at Stations 300

9.1.2 Model 9.2：Parts Stay on Conveyor During Processing 305

9.2 More on Transporters 306

9.3 Entity Reneging 308

9.3.1 Entity Balking and Reneging 308

9.3.2 Model 9.3：A Service Model with Balking and Reneging 309

9.4 Holding and Batching Entities 316

9.4.1 Modeling Options 316

9.4.2 Model 9.4：A Batching Process Example 317

9.5 Overlapping Resources 328

9.5.1 System Description 329

9.5.2 Model 9.5：A Tightly-Coupled Production System 330

9.6 A Few Miscellaneous Modeling Issues 350

9.6.1 Guided Transporters 350

9.6.2 Parallel Queues 350

9.6.3 Decision Logic 352

9.6.4 Continuous Modeling 352

9.7 Exercises 354

Chapter 10 Arena Customization and Integration 363

10.1 Model 10.1：Generating Entity Arrivals from Historical Data 363

10.2 Model 10.2：Recording and Charting Model Results in Microsoft R Excel 367

10.2.1 An Overview of ActiveX TM Automation and VBA 367

10.2.2 VBA Events at the Beginning of a Simulation Run 368

10.2.3 Storing Individual Call Data Using the VBA Module 372

10.2.4 Charting the Results and Cleaning Up at the End of the Run 374

10.3 Model 10.3：Organizing and Creating Your Own Reports 375

10.4 Model 10.4：Linking To and Embedding Other Files 381

10.4.1 Placing the Word File in the Arena Model 381

10.4.2 Establishing a Link to the Microsoft R PowerPoint R Presentation 383

10.4.3 Adding the Sound File 384

10.4.4 Tagging the Arena Objects for Identification in VBA 385

10.4.5 The Welcome Form 386

10.5 Creating Modules Using the Arena Professional Edition：Template 10.1 388

10.5.1 The Create from File Module 389

10.5.2 The Template Source File：Tpl_10_1.tpl 390

10.5.3 The Panel Icon and User View 390

10.5.4 The Module Logic and Operands 391

10.5.5 Uses of Templates 394

10.6 Summary 395

10.7 Exercises 395

Chapter 11 Further Statistical Issues 399

11.1 Random-Number Generation 399

11.2 Generating Random Variates 403

11.2.1 Discrete 404

11.2.2 Continuous 405

11.3 Nonstationary Poisson Processes 407

11.4 Variance Reduction 409

11.4.1 Common Random Numbers 410

11.4.2 Other Methods 418

11.5 Sequential Sampling 419

11.5.1 Terminating Models 419

11.5.2 Steady-State Models 424

11.6 Some Additional Capabilities of the Output Analyzer 427

11.6.1 Confidence Interval on Standard Deviation 427

11.6.2 Compare Variances 428

11.6.3 One-Way ANOVA 428

11.7 Designing and Executing Simulation Experiments 429

11.8 Exercises 429

Chapter 12 Conducting Simulation Studies 433

12.1 A Successful Simulation Study 433

12.2 Problem Formulation 436

12.3 Solution Methodology 437

12.4 System and Simulation Specification 438

12.5 Model Formulation and Construction 442

12.6 Verification and Validation 444

12.7 Experimentation and Analysis 447

12.8 Presenting and Preserving the Results 448

12.9 Disseminating the Model：The Arena Viewer 449

Appendix A A Functional Specification for The Washington Post 453

A.1 Introduction 453

A.1.1 Document Organization 453

A.1.2 Simulation Objectives 453

A.1.3 Purpose of the Functional Specification 454

A.1.4 Use of the Model 454

A.1.5 Hardware and Software Requirements 455

A.2 System Description and Modeling Approach 455

A.2.1 Model Timeline 455

A.2.2 Presses 455

A.2.3 Product Types 457

A.2.4 Press Packaging Lines 457

A.2.5 Tray System 457

A.2.6 Truck Arrivals 458

A.2.7 Docks 459

A.2.8 Palletizers 459

A.2.9 Manual Insertion Process 460

Example 460

A.3 Animation 461

A.4 Summary of Input and Output 461

A.4.1 Model Input 461

A.4.2 Model Output 462

A.5 Project Deliverables 464

A.5.1 Simulation Model Documentation 464

A.5.2 User’s Manual 464

A.5.3 Model Validation 464

A.5.4 Animation 464

A.6 Acceptance 464

Appendix B IIE/SM Contest Problems 469

B.1 First Annual Contest：The SM Superstore 469

B.2 Second Annual Contest：The SM Market 471

B.3 Third Annual Contest：Sally Model’s SM Pizza Shop 474

Appendix C A Refresher on Probability and Statistics 481

C.1 Probability Basics 481

C.2 Random Variables 483

C.2.1 Basics 483

C.2.2 Discrete 484

C.2.3 Continuous 486

C.2.4 Joint Distributions，Covariance，Correlation，and Independence 488

C.3 Sampling and Sampling Distributions 491

C.4 Point Estimation 492

C.5 Confidence Intervals 493

C.6 Hypothesis Tests 495

Appendix D Arena’s Probability Distributions 501

Beta 501

Continuous 502

Discrete 504

Erlang 505

Exponential 506

Gamma 507

Johnson 508

Lognormal 509

Normal 510

Poisson 511

Triangular 512

Uniform 513

Weibull 514

Appendix E Academic Software Installation Instructions 517

E.1 Authorization to Copy Software 517

E.2 Installing the Arena Software 517

E.3 System Requirements 518

E.4 Floppy Disks 518

References 523

References 523

Index 529

Index 529