Simulation Modeling and Analysis with ARENA
- 1st Edition - June 22, 2007
- Latest edition
- Authors: Tayfur Altiok, Benjamin Melamed
- Language: English
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… Read more
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Description
Description
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.
Key features
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
Readership
Readership
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.
Graduate students in business programs taking courses in industrial management, and related areas in quality control, modeling of complex systems.
Table of contents
Table of contents
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
Exercises
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
Control
2.4 DES Languages
Exercises
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
Exercises
Chapter 4
Random Number and Variate Generation
4.1 Variate and Process Generation
4.2 Variate Generation Using the Inverse Transform
Method
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
Exercises
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
Schedule
Exercises
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
Exercises
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
Exercises
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
Exercises
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
Replications
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
Exercises
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
Systems
Exercises
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
Exercises
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
System
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
Buffer
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
Exercises
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
Exercises
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
System
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
System
14.4.1 Request Arrivals and Transmission Network
Segment
14.4.2 Transmission Network Segment
14.4.3 Server Nodes Segment
14.4.4 Simulation Results
Exercises
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
References
Index
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
Exercises
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
Control
2.4 DES Languages
Exercises
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
Exercises
Chapter 4
Random Number and Variate Generation
4.1 Variate and Process Generation
4.2 Variate Generation Using the Inverse Transform
Method
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
Exercises
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
Schedule
Exercises
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
Exercises
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
Exercises
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
Exercises
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
Replications
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
Exercises
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
Systems
Exercises
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
Exercises
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
System
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
Buffer
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
Exercises
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
Exercises
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
System
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
System
14.4.1 Request Arrivals and Transmission Network
Segment
14.4.2 Transmission Network Segment
14.4.3 Server Nodes Segment
14.4.4 Simulation Results
Exercises
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
References
Index
Product details
Product details
- Edition: 1
- Latest edition
- Published: June 22, 2007
- Language: English
About the authors
About the authors
TA
Tayfur Altiok
Affiliations and expertise
Professor Department of Industrial and Systems Engineering, Rutgers University, New JerseyBM
Benjamin Melamed
Affiliations and expertise
Professor, Department of Management Science and Information Systems, Rutgers Business School, Rutgers University, New JerseyView book on ScienceDirect
View book on ScienceDirect
Read Simulation Modeling and Analysis with ARENA on ScienceDirect