Chapter 1 What is Simulation？

1.1 Modeling

1.1.1 What’s Being Modeled？

1.1.2 How About Just Playing with the System？

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

1.1.4 Physical Models

1.1.5 Logical （or Mathematical） Models

1.1.6 What Do You Do with a Logical Model？

1.2 Computer Simulation

1.2.1 Popularity and Advantages

1.2.2 The Bad News

1.2.3 Different Kinds of Simulations

1.3 How Simulations Get Done

1.3.1 By Hand

1.3.2 Programming in General-Purpose Languages

1.3.3 Simulation Languages

1.3.4 High-Level Simulators

1.3.5 Where Arena Fits In

1.4 When Simulations Are Used

1.4.1 The Early Years

1.4.2 The Formative Years

1.4.3 The Recent Past

1.4.4 The Present

1.4.5 The Future

Chapter 2 Fundamental Simulation Concepts

2.1 An Example

2.1.1 The System

2.1.2 Goals of the Study

2.2 Analysis Options

2.2.1 Educated Guessing

2.2.2 Queueing Theory

2.2.3 Mechanistic Simulation

2.3 Pieces of a Simulation Model

2.3.1 Entities

2.3.2 Attributes

2.3.3 （Global） Variables

2.3.4 Resources

2.3.5 Queues

2.3.6 Statistical Accumulators

2.3.7 Events

2.3.8 Simulation Clock

2.3.9 Starting and Stopping

2.4 Event-Driven Hand Simulation

2.4.1 Outline of the Action

2.4.2 Keeping Track

2.4.3 Carrying It Out

2.4.4 Finishing Up

2.5 Event and Process-Oriented Simulation

2.6 Randomness in Simulation

2.6.1 Random Input，Random Output

2.6.2 Replicating the Example

2.6.3 Comparing Alternatives

2.7 Overview of a Simulation Study

2.8 Exercises

Chapter 3 A Quick Peek at Arena

3.1 Starting Up

3.2 Browsing an Existing Model

3.2.1 Viewing the Model Window

3.2.2 The Arrive Module

3.2.3 The Server Module

3.2.4 The Depart Module

3.2.5 The Simulate Module

3.2.6 Module Connections

3.2.7 Dynamic Plots

3.2.8 Dressing Things Up

3.2.9 Running It

3.3 Understanding What Just Happened

3.3.1 Arena’s Modeling Orientation

3.3.2 Launching Entities Into the Model—The Arrive Module Revisited

3.3.3 Processing the Entity—The Server Module Revisited

3.3.4 Leaving the Modeled System—The Depart Module Revisited

3.3.5 Controlling the Run—The Simulate Module Revisited

3.4 Exercises

Chapter 4 Working with Arena

4.1 Basic Interaction

4.2 Menus

4.3 Toolbars

4.4 Help

4.5 Model Windows

4.6 Drawing

4.7 Printing

4.8 Running

4.9 Building the Simple Processing Model

Chapter 5 Modeling Basic Operations and Inputs

5.1 Model 5.1：An Electronic Assembly and Test System

5.1.1 Developing a Modeling Approach

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

5.1.3 Building the Model

5.1.4 Running the Model

5.1.5 Viewing the Results

5.2 Model 5.2：The Enhanced Electronic Assembly and Test System

5.2.1 Expanding Resource Representation：Schedules and States

5.2.2 Resource Schedules

5.2.3 Resource Failures

5.2.4 Saving Statistical Data

5.2.5 Results of Model 5.2

5.2.6 The Output Analyzer

5.3 Enhancing the Animation

5.3.1 Changing Animation Queues

5.3.2 Changing Entity Pictures

5.3.3 Changing Resource Pictures

5.3.4 Adding Plots and Variables

5.4 Input Analysis：Specifying Model Parameters and Distributions

5.4.1 Deterministic vs.Random Inputs

5.4.2 Collecting Data

5.4.3 Using Data

5.4.4 Fitting Input Distributions via the Input Analyzer

5.4.5 No Data？

5.4.6 Nonstationary Arrival Processes

5.4.7 Multivariate and Correlated Input Data

5.5 Summary and Forecast

5.6 Exercises

Chapter 6 Intermediate Modeling and Terminating Statistical Analysis

6.1 Model 6.1：A Small Manufacturing System

6.2 New Arena Concepts

6.2.1 Sequences

6.2.2 Variables and Expressions

6.2.3 Sets

6.3 The Modeling Approach

6.4 Building the Model

6.4.1 The Data Modules

6.4.2 The Logic Modules

6.4.3 Animation

6.4.4 Verification

6.5 Confidence Intervals for Terminating Simulations via the Output Analyzer

6.5.1 Time Frame of Simulations

6.5.2 Model 6.2：Modifying Model 6.1 for a Terminating Analysis

6.5.3 Strategy for Data Collection and Analysis

6.5.4 Confidence Intervals for Terminating Systems

6.5.5 Comparing Alternatives

6.6 Summary and Forecast

6.7 Exercises

Chapter 7 Entiry Transfer and Steady-State Statistical Analysis

7.1 Types of Entity Transfers

7.2 Resource-Constrained Transfers

7.3 Model 7.1：The Small Manufacturing System with Transporters

7.4 Conveyors

7.4.1 Model 7.2：The Small Manufacturing System with Nonaccumulating Conveyors

7.4.2 Model 7.3：The Small Manufacturing System with Accumulating Conveyors

7.5 Statistical Analysis of Steady-State Simulations

7.5.1 Warm Up and Run Length

7.5.2 Truncated Replications

7.5.3 Batching in a Single Run

7.5.4 Automatic Run-Time Confidence Intervals via Batch Means

7.5.5 What To Do？

7.5.6 Other Methods and Goals for Steady-State Statistical Analysis

7.6 Summary and Forecast

7.7 Exercises

Chapter 8 Detailed Modeling

8.1 Model 8.1：A Generic Call Center System

8.2 New Modeling Issues

8.3 Terminating or Steady-State

8.4 Modeling Approach

8.5 Defining the Data

8.6 Determine Maximum Arrival Rate and Increment Time Period

8.7 Create Arrivals and Direct to Service

8.8 Technical Support Calls

8.9 Sales Calls

8.10 Order-Status Calls

8.11 Finding and Fixing Model Errors

8.12 Animating the Model

8.13 Summary and Forecast

8.14 Exercises

Chapter 9 A Sampler of Further Modeling Issues and Techniques

9.1 Modeling Conveyors Using the Transfer Panel

9.1.1 Model 9.1：Finite Buffers at Stations

9.1.2 Model 9.2：Parts Stay on Conveyor During Processing

9.2 More on Transporters

9.3 Entity Reneging

9.3.1 Entity Balking and Reneging

9.3.2 Model 9.3：A Service Model with Balking and Reneging

9.4 Holding and Batching Entities

9.4.1 Modeling Options

9.4.2 Model 9.4：A Batching Process Example

9.5 Overlapping Resources

9.5.1 System Description

9.5.2 Model 9.5：A Tightly-Coupled Production System

9.6 A Few Miscellaneous Modeling Issues

9.6.1 Guided Transporters

9.6.2 Parallel Queues

9.6.3 Decision Logic

9.6.4 Continuous Modeling

9.7 Exercises

Chapter 10 Arena Customization and Integration

10.1 Model 10.1：Generating Entity Arrivals from Historical Data

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

10.2.1 An Overview of ActiveX TM Automation and VBA

10.2.2 VBA Events at the Beginning of a Simulation Run

10.2.3 Storing Individual Call Data Using the VBA Module

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

10.3 Model 10.3：Organizing and Creating Your Own Reports

10.4 Model 10.4：Linking To and Embedding Other Files

10.4.1 Placing the Word File in the Arena Model

10.4.2 Establishing a Link to the Microsoft R PowerPoint R Presentation

10.4.3 Adding the Sound File

10.4.4 Tagging the Arena Objects for Identification in VBA

10.4.5 The Welcome Form

10.5 Creating Modules Using the Arena Professional Edition：Template 10.1

10.5.1 The Create from File Module

10.5.2 The Template Source File：Tpl_10_1.tpl

10.5.3 The Panel Icon and User View

10.5.4 The Module Logic and Operands

10.5.5 Uses of Templates

10.6 Summary

10.7 Exercises

Chapter 11 Further Statistical Issues

11.1 Random-Number Generation

11.2 Generating Random Variates

11.2.1 Discrete

11.2.2 Continuous

11.3 Nonstationary Poisson Processes

11.4 Variance Reduction

11.4.1 Common Random Numbers

11.4.2 Other Methods

11.5 Sequential Sampling

11.5.1 Terminating Models

11.5.2 Steady-State Models

11.6 Some Additional Capabilities of the Output Analyzer

11.6.1 Confidence Interval on Standard Deviation

11.6.2 Compare Variances

11.6.3 One-Way ANOVA

11.7 Designing and Executing Simulation Experiments

11.8 Exercises

Chapter 12 Conducting Simulation Studies

12.1 A Successful Simulation Study

12.2 Problem Formulation

12.3 Solution Methodology

12.4 System and Simulation Specification

12.5 Model Formulation and Construction

12.6 Verification and Validation

12.7 Experimentation and Analysis

12.8 Presenting and Preserving the Results

12.9 Disseminating the Model：The Arena Viewer

Appendix A A Functional Specification for The Washington Post

A.1 Introduction

A.1.1 Document Organization

A.1.2 Simulation Objectives

A.1.3 Purpose of the Functional Specification

A.1.4 Use of the Model

A.1.5 Hardware and Software Requirements

A.2 System Description and Modeling Approach

A.2.1 Model Timeline

A.2.2 Presses

A.2.3 Product Types

A.2.4 Press Packaging Lines

A.2.5 Tray System

A.2.6 Truck Arrivals

A.2.7 Docks

A.2.8 Palletizers

A.2.9 Manual Insertion Process

Example

A.3 Animation

A.4 Summary of Input and Output

A.4.1 Model Input

A.4.2 Model Output

A.5 Project Deliverables

A.5.1 Simulation Model Documentation

A.5.2 User’s Manual

A.5.3 Model Validation

A.5.4 Animation

A.6 Acceptance

Appendix B IIE/SM Contest Problems

B.1 First Annual Contest：The SM Superstore

B.2 Second Annual Contest：The SM Market

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

Appendix C A Refresher on Probability and Statistics

C.1 Probability Basics

C.2 Random Variables

C.2.1 Basics

C.2.2 Discrete

C.2.3 Continuous

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

C.3 Sampling and Sampling Distributions

C.4 Point Estimation

C.5 Confidence Intervals

C.6 Hypothesis Tests

Appendix D Arena’s Probability Distributions

Beta

Continuous

Discrete

Erlang

Exponential

Gamma

Johnson

Lognormal

Normal

Poisson

Triangular

Uniform

Weibull

Appendix E Academic Software Installation Instructions

E.1 Authorization to Copy Software

E.2 Installing the Arena Software

E.3 System Requirements

E.4 Floppy Disks

References

References

Index

Index