Simulation Modeling Handbook: A Practical

The use of simulation modeling and analysis is becoming increasingly more popular as a technique for improving or investigating process performance. This book is a practical, easy-to-follow reference that offers up-to-date information and step-by-step procedures for conducting simulation studies. It provides sample simulation project support material, including checklists, data-collection forms, and sample simulation project reports and publications to facilitate practitioners' efforts in conducting simulation modeling and analysis projects.Simulation Modeling Handbook: A Practical Approach has two major advantages over other treatments. First, it is independent of any particular simulation software, allowing readers to use any commercial package or programming language. Second, it was written to insulate practitioners from unnecessary simulation theory that does not focus on their average, practical needs.As the popularity of simulation studies continues to grow, the planning and execution of these projects, more and more engineering and management professionals will be called upon to perform these tasks. With its simple, no-nonsense approach and focus on application rather than theory, this comprehensive and easy-to-understand guide is the ideal vehicle for acquiring the background and skills needed to undertake effective simulation projects.Features· Presents step-by-step procedures for conducting successful simulation modeling and analysis· Addresses every phase of performing simulations, from formulating the problem to presenting study results and recommendations· Uses approaches applicable regardless of the specific simulation or software used· Includes a summary of the major simulation software packages and discusses the pros and cons of using general purpose programming languages

Introduction
Introduction	p. 1
Simulation Modeling and Analysis	p. 2
Other Types of Simulation Models	p. 3
Purposes of Simulation	p. 3
Advantages to Simulation	p. 4
Disadvantages to Simulation	p. 5
Other Considerations	p. 6
Famous Simulation Quotes	p. 7
Basic Simulation Concepts	p. 8
Additional Basic Simulation Issues	p. 18
Summary	p. 18
Chapter Problems	p. 19
Problem Formulation
Introduction	p. 1
Formal Problem Statement	p. 1
Orientation	p. 4
Project Objectives	p. 6
Summary	p. 10
Chapter Problems	p. 11
Project Planning
Introduction	p. 1
Project Management Concepts	p. 2
Simulation Project Manager Functions	p. 6
Developing the Simulation Project Plan	p. 13
Compressing Projects	p. 18
Example Gantt Chart	p. 20
Advanced Project Management Concepts	p. 20
Project Management Software Packages	p. 31
Summary	p. 32
Chapter Problems	p. 35
Sample LRC	p. 37
Sample Gantt Chart	p. 38
System Definition
Introduction	p. 1
System Classifications	p. 2
High-Level Flow Chart Basics	p. 5
Components and Events to Model	p. 8
Data to Be Included in the Model	p. 23
Output Data	p. 26
Summary	p. 29
Chapter Problems	p. 29
Input Data Collection and Analysis
Introduction	p. 1
Sources for Input Data	p. 2
Collecting Input Data	p. 4
Deterministic versus Probabilistic Data	p. 6
Discrete vs. Continuous Data	p. 7
Common Input Data Distributions	p. 7
Less Common Distributions	p. 15
Offset Combination Distributions	p. 18
Analyzing Input Data	p. 19
How Much Data Needs to Be Collected	p. 25
What Happens If I Cannot Fit the Input Data?	p. 26
Software Implementations for Data Fitting	p. 27
Summary	p. 28
Chapter Questions	p. 29
Model Translation
Introduction	p. 1
Simulation Program Selection	p. 2
Model Translation Section Content	p. 3
Program Organization	p. 8
Summary	p. 13
Chapter Problems	p. 14
Model Translation Check List	p. 15
Verification
Introduction	p. 1
Divide-and-Conquer Approach	p. 2
Animation	p. 3
Advancing the Simulation Clock Event by Event	p. 8
Writing to an Output File	p. 8
Summary	p. 10
Chapter Problems	p. 11
Validation
Introduction	p. 1
Assumptions	p. 2
Simplifications	p. 2
Oversights	p. 3
Limitations	p. 3
Need for Validation	p. 4
Two Types of Validation	p. 4
Face Validity	p. 4
Statistical Validity	p. 5
Validation Data Analysis Process	p. 7
When a Model Cannot Be Statistically Validated and What to Do about It	p. 16
Summary	p. 17
Chapter Problems	p. 18
Experimental Design
Introduction	p. 1
Factors and Levels	p. 2
Two Alternative Experimental Designs	p. 2
One-Factor Experimental Designs	p. 5
Two-Factor Experimental Designs	p. 6
Multifactor Experimental Designs	p. 7
2k Experimental Designs	p. 9
Experimental Alternative Factor Interactions	p. 11
Refining the Experimental Alternatives	p. 11
Summary	p. 11
Chapter Problems	p. 12
Analysis
Introduction	p. 1
Terminating System Analysis	p. 2
Nonterminating System Analysis	p. 22
Summary	p. 30
Chapter Problems	p. 30
Project Reports and Presentations
Introduction	p. 1
Written Report Guidelines	p. 2
Executive Summary	p. 2
Equations	p. 2
Importing Screen Captures	p. 2
Presentation Guidelines	p. 4
Presentation Media	p. 4
Electronic Presentation Software Issues	p. 6
Actual Presentation	p. 9
Summary	p. 12
Chapter Questions	p. 12
Training Simulators
Introduction	p. 1
Problem Formulation	p. 6
Project Planning	p. 7
System Definition	p. 9
Input Data Collection	p. 14
Model Translation	p. 21
Verification	p. 24
Validation	p. 24
Implementation	p. 39
Summary	p. 42
Chapter Problems	p. 42
Examples
Combined Continuous and Discrete Simulation Models in the High-Speed Food Industry	p. 2
Operation of Airport Security Checkpoints under Increased Threat Conditions	p. 9
Modeling and Analysis of Commercial Aircraft Passenger Loading Sequencing	p. 20
Multitheater Movie Complex	p. 41
Will-Call Operations Simulation Modeling and Analysis	p. 52
ARENA User's Minimanual
Introduction	p. 2
ARENA User Interface	p. 2
Frequently Used Model Blocks	p. 4
Frequently Used Experiment Elements	p. 8
General Approach for Developing a Simple Nonanimated Model	p. 14
Building the Model	p. 14
Filling in the Experimental Data	p. 15
Filling in the Model Data	p. 17
Running the Model	p. 18
Basic Animation of the Model	p. 19
Additional Queue Techniques	p. 25
Modeling Transporters	p. 32
Modeling Conveyors	p. 46
Outputting Data to a File for Validation or Comparison Purposes	p. 58
Input Analyzer	p. 60
Output Analyzer	p. 66
Simulation Using AutoMod and AutoStat
Introduction	p. 2
Introduction to the AutoMod Tutorial	p. 3
Using the Mouse	p. 4
Section 1: Getting Started	p. 4
Section 2: Building a Model	p. 7
Section 3: Changing Views	p. 17
Section 4: Adding Queues and Resources	p. 22
Section 5: Completing the Conveyor System	p. 28
Section 6: Creating an AGV System	p. 40
Defining and Placing Control Points	p. 48
Defining Vehicles	p. 51
Scheduling Vehicles	p. 53
Adding the Inspection, Labeling, Repair, and Rejection Processes	p. 58
AutoMod Tutorial Summary	p. 63
Basic Statistical Analysis Using AutoStat	p. 64
Why Use AutoStat?	p. 64
Calculating Confidence Intervals	p. 64
Performing Statistical Analysis with AutoStat	p. 65
Opening a Model in AutoStat	p. 66
Defining a Single Scenario Analysis	p. 68
Making Runs	p. 69
Defining Responses	p. 70
Displaying the Results	p. 70
Statistical Analysis Using AutoStat Summary	p. 75
Simpak User's Manual
Introduction	p. 1
Random Variate Routines	p. 2
Schedule Initializer Subprogram (INITIAL)	p. 3
SIMPAK Scheduler (SCHED)	p. 3
Event Remover (REMOVER)	p. 3
Example Problem 1	p. 4
List Processing Initializer (LISTINIT)	p. 6
List Creator (GRAB)	p. 7
List Inserter (LISTPUT)	p. 7
List Retriever (LISTR V)	p. 7
List Extender (LISTEXTN)	p. 8
List Remover (LISTFREE)	p. 8
Example Problem 2	p. 9
Discussion	p. 12
SIMPAK Reference Sheet	p. 12
Statistical Tables	p. 1
Course Outline	p. 1
Introduction	p. 1
Basic Simulation Process	p. 2
Introduction to Models	p. 4
Problem Formulation	p. 8
Project Planning	p. 12
Project Planning II	p. 15
System Definition	p. 17
Input Data Collection and Analysis	p. 24
Model Translation	p. 32
Verification	p. 35
Validation	p. 36
Experimental Design	p. 41
Analysis	p. 43
Analysis II	p. 46
Analysis III	p. 47
Analysis IV	p. 49
Analysis V	p. 51
Reports and Presentations	p. 52
Index	p. 1
Table of Contents provided by Rittenhouse. All Rights Reserved.

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Simulation Modeling Handbook: A Practical Approach

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