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Simulation Modeling and Analysis with ARENA

Simulation Modeling and Analysis with ARENA, 1st Edition

Simulation Modeling and Analysis with ARENA, 1st Edition,Tayfur Altiok,Benjamin Melamed,ISBN9780123705235


Academic Press



260 X 184

A Concise text that includes the most up-to-date principles of simulation modeling as well as the popular, in demand ARENA simulation software package.

Print Book


In Stock

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USD 98.95

Key Features

· Introduces the concept of discrete event Monte Carlo simulation, the most commonly used methodology for modeling and analysis of complex systems
· Covers essential workings of the popular animated simulation language, ARENA, including set-up, design parameters, input data, and output analysis, along with a wide variety of sample model applications from production lines to transportation systems
· Reviews elements of statistics, probability, and stochastic processes relevant to simulation modeling
* Ample end-of-chapter problems and full Solutions Manual
* Includes CD with sample ARENA modeling programs


Simulation Modeling and Analysis with Arena is a highly readable textbook which treats the essentials of the Monte Carlo discrete-event simulation methodology, and does so in the context of a popular Arena simulation environment.” It treats simulation modeling as an in-vitro laboratory that facilitates the understanding of complex systems and experimentation with what-if scenarios in order to estimate their performance metrics. The book contains chapters on the simulation modeling methodology and the underpinnings of discrete-event systems, as well as the relevant underlying probability, statistics, stochastic processes, input analysis, model validation and output analysis. All simulation-related concepts are illustrated in numerous Arena examples, encompassing production lines, manufacturing and inventory systems, transportation systems, and computer information systems in networked settings.


Junior and Senior undergraduate students taking required courses in “Simulation,” and related courses in “Simulation and Modeling,” and “Modeling and Analysis,” often mandated for majors in Industrial and Mechanical engineering programs, as well as offered for students in other engineering disciplines, including civil, electrical, and chemical engineering, among others.
Graduate students in business programs taking courses in industrial management, and related areas in quality control, modeling of complex systems.

Tayfur Altiok

Affiliations and Expertise

Professor Department of Industrial and Systems Engineering, Rutgers University, New Jersey

Benjamin Melamed

Affiliations and Expertise

Professor, Department of Management Science and Information Systems, Rutgers Business School, Rutgers University, New Jersey

Simulation Modeling and Analysis with ARENA, 1st Edition

Chapter 1
Introduction to Simulation Modeling
1.1 Systems and Models
1.2 Analytical Versus Simulation Modeling
1.3 Simulation Modeling and Analysis
1.4 Simulation Worldviews
1.5 Model Building
1.6 Simulation Costs and Risks
1.7 Example: A Production Control Problem
1.8 Project Report
Chapter 2
Discrete Event Simulation
2.1 Elements of Discrete Event Simulation
2.2 Examples of DES Models
2.2.1 Single Machine
2.2.2 Single Machine with Failures
2.2.3 Single Machine with an Inspection Station and Associated Inventory
2.3 Monte Carlo Sampling and Histories
2.3.1 Example: Work Station Subject to Failures and Inventory
2.4 DES Languages
Chapter 3
Elements of Probability and Statistics
3.1 Elementary Probability Theory
3.1.1 Probability Spaces
3.1.2 Conditional Probabilities
3.1.3 Dependence and Independence
3.2 Random Variables
3.3 Distribution Functions
3.3.1 Probability Mass Functions
3.3.2 Cumulative Distribution Functions
3.3.3 Probability Density Functions
3.3.4 Joint Distributions
3.4 Expectations
3.5 Moments
3.6 Correlations
3.7 Common Discrete Distributions
3.7.1 Generic Discrete Distribution
3.7.2 Bernoulli Distribution
3.7.3 Binomial Distribution
3.7.4 Geometric Distribution
3.7.5 Poisson Distribution
3.8 Common Continuous Distributions
3.8.1 Uniform Distribution
3.8.2 Step Distribution
3.8.3 Triangular Distribution
3.8.4 Exponential Distribution
3.8.5 Normal Distribution
3.8.6 Lognormal Distribution
3.8.7 Gamma Distribution
3.8.8 Student´s t Distribution
3.8.9 F Distribution
3.8.10 Beta Distribution
3.8.11 Weibull Distribution
3.9 Stochastic Processes
3.9.1 Iid Processes
3.9.2 Poisson Processes
3.9.3 Regenerative (Renewal) Processes
3.9.4 Markov Processes
3.10 Estimation
3.11 Hypothesis Testing
Chapter 4
Random Number and Variate Generation
4.1 Variate and Process Generation
4.2 Variate Generation Using the Inverse Transform
4.2.1 Generation of Uniform Variates
4.2.2 Generation of Exponential Variates
4.2.3 Generation of Discrete Variates
4.2.4 Generation of Step Variates from Histograms
4.3 Process Generation
4.3.1 Iid Process Generation
4.3.2 Non-Iid Process Generation
Chapter 5
Arena Basics
5.1 Arena Home Screen
5.1.1 Menu Bar
5.1.2 Project Bar
5.1.3 Standard Toolbar
5.1.4 Draw and View Bars
5.1.5 Animate and Animate Transfer Bars
5.1.6 Run Interaction Bar
5.1.7 Integration Bar
5.1.8 Debug Bar
5.2 Example: A Simple Workstation
5.3 Arena Data Storage Objects
5.3.1 Variables
5.3.2 Expressions
5.3.3 Attributes
5.4 Arena Output Statistics Collection
5.4.1 Statistics Collection via the Statistic Module
5.4.2 Statistics Collection via the Record Module
5.5 Arena Simulation and Output Reports
5.6 Example: Two Processes in Series
5.7 Example: A Hospital Emergency Room
5.7.1 Problem Statement
5.7.2 Arena Model
5.7.3 Emergency Room Segment
5.7.4 On-Call Doctor Segment
5.7.5 Statistics Collection
5.7.6 Simulation Output
5.8 Specifying Time-Dependent Parameters via a
Chapter 6
Model Testing and Debugging Facilities
6.1 Facilities for Model Construction
6.2 Facilities for Model Checking
6.3 Facilities for Model Run Control
6.3.1 Run Modes
6.3.2 Mouse-Based Run Control
6.3.3 Keyboard-Based Run Control
6.4 Examples of Run Tracing
6.4.1 Example: Open-Ended Tracing
6.4.2 Example: Tracing Selected Blocks
6.4.3 Example: Tracing Selected Entities
6.5 Visualization and Animation
6.5.1 Animate Connectors Button
6.5.2 Animate Toolbar
6.5.3 Animate Transfer Toolbar
6.6 Arena Help Facilities
6.6.1 Help Menu
6.6.2 Help Button
Chapter 7
Input Analysis
7.1 Data Collection
7.2 Data Analysis
7.3 Modeling Time Series Data
7.3.1 Method of Moments
7.3.2 Maximal Likelihood Estimation Method
7.4 Arena Input Analyzer
7.5 Goodness-of-Fit Tests for Distributions
7.5.1 Chi-Square Test
7.5.2 Kolmogorov-Smirnov (K-S) Test
7.6 Multimodal Distributions
Chapter 8
Model Goodness: Verification and Validation
8.1 Model Verification via Inspection of Test Runs
8.1.1 Input Parameters and Output Statistics
8.1.2 Using a Debugger
8.1.3 Using Animation
8.1.4 Sanity Checks
8.2 Model Verification via Performance Analysis
8.2.1 Generic Workstation as a Queueing System
8.2.2 Queueing Processes and Parameters
8.2.3 Service Disciplines
8.2.4 Queueing Performance Measures
8.2.5 Regenerative Queueing Systems and Busy Cycles
8.2.6 Throughput
8.2.7 Little´s Formula
8.2.8 Steady-State Flow Conservation
8.2.9 PASTA Property
8.3 Examples of Model Verification
8.3.1 Model Verification in a Single Workstation
8.3.2 Model Verification in Tandem Workstations
8.4 Model Validation
Chapter 9
Output Analysis
9.1 Terminating and Steady-State Simulation Models
9.1.1 Terminating Simulation Models
9.1.2 Steady-State Simulation Models
9.2 Statistics Collection from Replications
9.2.1 Statistics Collection Using Independent
9.2.2 Statistics Collection Using Regeneration Points and Batch Means
9.3 Point Estimation
9.3.1 Point Estimation from Replications
9.3.2 Point Estimation in Arena
9.4 Confidence Interval Estimation
9.4.1 Confidence Intervals for Terminating Simulations
9.4.2 Confidence Intervals for Steady-State Simulations
9.4.3 Confidence Interval Estimation in Arena
9.5 Output Analysis via Standard Arena Output
9.5.1 Working Example: A Workstation with
Two Types of Parts
9.5.2 Observation Collection
9.5.3 Output Summary
9.5.4 Statistics Summary: Multiple Replications
9.6 Output Analysis via the Arena Output Analyzer
9.6.1 Data Collection
9.6.2 Graphical Statistics
9.6.3 Batching Data for Independent Observations
9.6.4 Confidence Intervals for Means and Variances
9.6.5 Comparing Means and Variances
9.6.6 Point Estimates for Correlations
9.7 Parametric Analysis via the Arena Process Analyzer
Chapter 10
Correlation Analysis
10.1 Correlation in Input Analysis
10.2 Correlation in Output Analysis
10.3 Autocorrelation Modeling with TES Processes
10.4 Introduction to TES Modeling
10.4.1 Background TES Processes
10.4.2 Foreground TES Processes
10.4.3 Inversion of Distribution Functions
10.5 Generation of TES Sequences
Generation of TESþ Sequences
Generation of TES_ Sequences
Combining TES Generation Algorithms
10.6 Example: Correlation Analysis in Manufacturing
Chapter 11
Modeling Production Lines
11.1 Production Lines
11.2 Models of Production Lines
11.3 Example: A Packaging Line
11.3.1 An Arena Model
11.3.2 Manufacturing Process Modules
11.3.3 Model Blocking Using the Hold Module
11.3.4 Resources and Queues
11.3.5 Statistics Collection
11.3.6 Simulation Output Reports
11.4 Understanding System Behavior and Model Verification
11.5 Modeling Production Lines via Indexed Queues and Resources
11.6 An Alternative Method of Modeling Blocking
11.7 Modeling Machine Failures
11.8 Estimating Distributions of Sojourn Times
11.9 Batch Processing
11.10 Assembly Operations
11.11 Model Verification for Production Lines
Chapter 12
Modeling Supply Chain Systems
12.1 Example: A Production/Inventory System
12.1.1 Problem Statement
12.1.2 Arena Model
12.1.3 Inventory Management Segment
12.1.4 Demand Management Segment
12.1.5 Statistics Collection
12.1.6 Simulation Output
12.1.7 Experimentation and Analysis
12.2 Example: A Multiproduct Production/Inventory
12.2.1 Problem Statement
12.2.2 Arena Model
12.2.3 Inventory Management Segment
12.2.4 Demand Management Segment
12.2.5 Model Input Parameters and Statistics
12.2.6 Simulation Results
12.3 Example: A Multiechelon Supply Chain
12.3.1 Problem Statement
12.3.2 Arena Model
12.3.3 Inventory Management Segment for Retailer
12.3.4 Inventory Management Segment
for Distribution Center
12.3.5 Inventory Management Segment for Output
12.3.6 Production/Inventory Management Segment
for Input Buffer
12.3.7 Inventory Management Segment for Supplier
12.3.8 Statistics Collection
12.3.9 Simulation Results
Chapter 13
Modeling Transportation Systems
13.1 Advanced Transfer Template Panel
13.2 Animate Transfer Toolbar
13.3 Example: A Bulk-Material Port
13.3.1 Ship Arrivals
13.3.2 Tug Boat Operations
13.3.3 Coal-Loading Operations
13.3.4 Tidal Window Modulation
13.3.5 Simulation Results
13.4 Example: A Toll Plaza
13.4.1 Arrivals Generation
13.4.2 Dispatching Cars to Tollbooths
13.4.3 Serving Cars at Tollbooths
13.4.4 Simulation Results for the Toll Plaza Model
13.5 Example: A Gear Manufacturing Job Shop
13.5.1 Gear Job Arrivals
13.5.2 Gear Transportation
13.5.3 Gear Processing
13.5.4 Simulation Results for the Gear Manufacturing
Job Shop Model
13.6 Example: Sets Version of the Gear Manufacturing
Job Shop Model
Chapter 14
Modeling Computer Information Systems
14.1 Client/Server System Architectures
14.1.1 Message-Based Communications
14.1.2 Client Hosts
14.1.3 Server Hosts
14.2 Communications Networks
14.3 Two-Tier Client/Server Example: A Human Resources
14.3.1 Client Nodes Segment
14.3.2 Communications Network Segment
14.3.3 Server Node Segment
14.3.4 Simulation Results
14.4 Three-Tier Client/Server Example: An Online Bookseller
14.4.1 Request Arrivals and Transmission Network
14.4.2 Transmission Network Segment
14.4.3 Server Nodes Segment
14.4.4 Simulation Results
Appendix A
Frequently Used Arena Constructs
A.1 Frequently Used Arena Built-in Variables
A.1.1 Entity-Related Attributes and Variables
A.1.2 Simulation Time Variables
A.1.3 Expressions
A.1.4 General-Purpose Global Variables
A.1.5 Queue Variables
A.1.6 Resource Variables
A.1.7 Statistics Collection Variables
A.1.8 Transporter Variables
A.1.9 Miscellaneous Variables and Functions
A.2 Frequently Used Arena Modules
A.2.1 Access Module (Advanced Transfer)
A.2.2 Assign Module (Basic Process)
A.2.3 Batch Module (Basic Process)
A.2.4 Create Module (Basic Process)
A.2.5 Decide Module (Basic Process)
A.2.6 Delay Module (Advanced Process)
A.2.7 Dispose Module (Basic Process)
A.2.8 Dropoff Module (Advanced Process)
A.2.9 Free Module (Advanced Transfer)
A.2.10 Halt Module (Advanced Transfer)
A.2.11 Hold Module (Advanced Process)
A.2.12 Match Module (Advanced Process)
A.2.13 PickStation Module (Advanced Transfer)
A.2.14 Pickup Module (Advanced Process)
A.2.15 Process Module (Basic Process)
A.2.16 ReadWrite Module (Advanced Process)
A.2.17 Record Module (Basic Process)
A.2.18 Release Module (Advanced Process)
A.2.19 Remove Module (Advanced Process)
A.2.20 Request Module (Advanced Transfer)
A.2.21 Route Module (Advanced Transfer)
A.2.22 Search Module (Advanced Process)
A.2.23 Seize Module (Advanced Process)
A.2.24 Separate Module (Basic Process)
A.2.25 Signal Module (Advanced Process)
A.2.26 Station Module (Advanced Transfer)
A.2.27 Store Module (Advanced Process)
A.2.28 Transport Module (Advanced Transfer)
A.2.29 Unstore Module (Advanced Process)
A.2.30 VBA Block (Blocks)
Appendix B
VBA in Arena
B.1 Arena’s Object Model
B.2 Arena’s Type Library
B.2.1 Resolving Object Name Ambiguities
B.2.2 Obtaining Access to the Application Object
B.3 Arena VBA Events
B.4 Example: Using VBA in Arena
B.4.1 Changing Inventory Parameters Just Before
a Simulation Run
B.4.2 Changing Inventory Parameters during
a Simulation Run
B.4.3 Changing Customer Arrival Distributions Just before
a Simulation Run
B.4.3 Writing Arena Data to Excel via VBA Code
B.4.4 Reading Arena Data from Excel via VBA Code
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