Simulation Modeling and Arena

Häftad, Engelska, 2015

AvManuel D. Rossetti,Manuel D. (University of Arkansas) Rossetti

1 549 kr

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Emphasizes a hands-on approach to learning statistical analysis and model building through the use of comprehensive examples, problems sets, and software applicationsWith a unique blend of theory and applications, Simulation Modeling and Arena®, Second Edition integrates coverage of statistical analysis and model building to emphasize the importance of both topics in simulation. Featuring introductory coverage on how simulation works and why it matters, the Second Edition expands coverage on static simulation and the applications of spreadsheets to perform simulation.The new edition also introduces the use of the open source statistical package, R, for both performing statistical testing and fitting distributions. In addition, the models are presented in a clear and precise pseudo-code form, which aids in understanding and model communication. Simulation Modeling and Arena, Second Edition also features: Updated coverage of necessary statistical modeling concepts such as confidence interval construction, hypothesis testing, and parameter estimationAdditional examples of the simulation clock within discrete event simulation modeling involving the mechanics of time advancement by hand simulationA guide to the Arena Run Controller, which features a debugging scenarioNew homework problems that cover a wider range of engineering applications in transportation, logistics, healthcare, and computer scienceA related website with an Instructor’s Solutions Manual, PowerPoint® slides, test bank questions, and data sets for each chapter Simulation Modeling and Arena, Second Edition is an ideal textbook for upper-undergraduate and graduate courses in modeling and simulation within statistics, mathematics, industrial and civil engineering, construction management, business, computer science, and other departments where simulation is practiced. The book is also an excellent reference for professionals interested in mathematical modeling, simulation, and Arena.

Produktinformation

Utgivningsdatum2015-07-28
Mått173 x 252 x 38 mm
Vikt1 225 g
FormatHäftad
SpråkEngelska
Antal sidor744
Upplaga2
FörlagJohn Wiley & Sons Inc
ISBN9781118607916

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Manuel D. Rossetti, PhD, is Professor in the Industrial Engineering Department at the University of Arkansas. Dr. Rossetti has published over 85 journal and conference articles. In 2013, he received the Charles and Nadine Baum Teaching Award for the University of Arkansas, the highest teaching honor bestowed at the university. His research interests include the design, analysis, and optimization of logistics, manufacturing, health care, and transportation systems using computer simulation and operations research techniques.

Preface xviiAcknowledgments xixIntroduction xxi1 Simulation Modeling 11.1 Simulation Modeling 11.2 Why Simulate? 21.3 Types of Computer Simulation 31.4 Descriptive or Prescriptive? 61.5 Randomness in Simulation 71.6 Simulation Languages 71.7 Simulation Methodology 81.8 Organization of the Book 14Exercises 152 Generating Randomness in Simulation 172.1 Stochastic Simulation 172.2 Random Numbers 182.3 Random Number Generators 192.4 Testing Random Numbers 242.4.1 Distributional Tests 242.4.2 Testing Independence 332.5 Random Variates 372.5.1 Inverse Transform 372.5.2 Convolution 452.5.3 Acceptance/Rejection 462.5.4 Mixture Distributions, Truncated Distributions, and Shifted Random Variables 492.6 Summary 53Exercises 533 Spreadsheet Simulation 613.1 Simulation in a Spreadsheet Environment 613.2 Useful Spreadsheet Functions and Methods 623.2.1 Using RAND() and RANDBETWEEN() 623.2.2 Using VLOOKUP() 653.2.3 Using Data Tables to Repeatedly Sample 663.2.4 Using VBA 683.3 Example Spreadsheet Simulations 693.3.1 Simple Monte Carlo Integration 693.3.2 The Classic News Vendor Inventory Problem 733.3.3 Simulating a Random Cash Flow 763.4 Introductory Statistical Concepts 793.4.1 Point Estimates and Confidence Intervals 793.4.2 Determining the Sample Size 803.5 Summary 85Exercises 854 Introduction to Simulation in ArenaTM 954.1 Introduction 954.2 The ArenaTM Environment 964.3 Performing Simple Monte-Carlo Simulations using ArenaTM 984.3.1 Re-Doing Area Estimation with ArenaTM 994.3.2 Re-Doing the News Vendor Problem with ArenaTM 1024.4 How the Discrete-Event Clock Works 1054.5 Modeling a Simple Discrete-Event Dynamic System 1094.5.1 A Drive through Pharmacy 1094.5.2 Modeling the System 1104.5.3 Implementing the Model in ArenaTM 1124.5.4 Specify the Arrival Process 1134.5.5 Specify the Resources 1154.5.6 Specify the Process 1164.5.7 Specify Run Parameters 1174.5.8 Analyze the Results 1194.6 Extending the Drive Through Pharmacy Model 1224.7 Animating the Drive Through Pharmacy Model 1254.8 Getting Help in ArenaTM 1324.9 SIMAN and the Run Controller 1344.9.1 SIMAN MOD and EXP Files 1344.9.2 Using the Run Controller 1384.10 How ArenaTM Manages Entities and Events 1464.11 Summary 150Exercises 1515 Basic Process Modeling 1635.1 Elements of Process-Oriented Simulation 1635.2 Entities, Attributes, and Variables 1645.3 Creating and Disposing of Entities 1665.4 Defining Variables and Attributes 1705.5 Processing Entities 1755.6 Attributes, Variables, and some I/O 1775.6.1 Modifying the Pharmacy Model 1775.6.2 Using the ASSIGN Module 1805.6.3 Using the READWRITE Module 1825.6.4 Using the RECORD Module 1865.6.5 Animating a Variable 1875.6.6 Running the Model 1895.7 Flow of Control in Arena 1925.7.1 Logical and Probabilistic Conditions 1925.7.2 Iterative Looping 1975.7.3 Example: Iterative Looping, Expressions, and Sub-models 1985.8 Batching and Separating Entities 2135.8.1 Example: Tie-Dye T-Shirts 2135.9 Summary 225Exercises 2276 Modeling Randomness in Simulation 2356.1 Random Variables and Probability Distributions 2356.2 Modeling with Discrete Distributions 2406.3 Modeling with Continuous Distributions 2426.4 Input Distribution Modeling 2446.5 Fitting Discrete Distributions 2456.5.1 Fitting a Poisson Distribution 2466.5.2 Visualizing the Data 2466.5.3 Statistical Analysis of the Data 2506.5.4 Checking the Goodness of Fit of the Model 2536.6 Fitting Continuous Distributions 2576.6.1 Visualizing the Data 2576.6.2 Statistically Summarize the Data 2586.6.3 Hypothesizing and Testing a Distribution 2606.6.4 Visualizing the Fit 2666.7 Using the Input Analyzer 2716.8 Additional Input Modeling Concepts 2806.9 Modeling Randomness in ArenaTM 2836.9.1 Conceptualizing the Model 2846.9.2 Implementing the Model 2856.10 Summary 297Exercises 2987 Analyzing Simulation Output 3037.1 Types of Statistical Variables 3047.2 Types of Simulation With Respect To Output Analysis 3107.3 Analysis of Finite Horizon Simulations 3117.3.1 Determining the Number of Replications 3137.3.2 Finite Horizon Example 3157.3.3 Sequential Sampling for Finite Horizon Simulations 3237.4 Analysis of Infinite Horizon Simulations 3267.4.1 Assessing the Effect of Initial Conditions 3327.4.2 Performing the Method of Replication-Deletion 3387.4.3 Looking for the Warm up Period in the Output Analyzer 3417.4.4 The Method of Batch Means 3547.4.5 Performing the Method of Batch Means 3587.5 Comparing System Configurations 3627.5.1 Comparing Two Systems 3627.5.2 Analyzing Multiple Systems 3827.6 Summary 395Exercises 3968 Modeling Queueing and Inventory Systems 4058.1 Introduction 4058.2 Single Line Queueing Stations 4068.2.1 Queueing Notation 4088.2.2 Little’s Formula 4108.2.3 Deriving Formulas for Markovian Single Queue Systems 4138.3 Examples and Applications of Queueing Analysis 4198.3.1 Infinite Queue Examples 4198.3.2 Finite Queue Examples 4248.4 Non-Markovian Queues and Approximations 4308.5 Simulating Single Queues in ArenaTM 4318.5.1 Machine Interference Optimization Model 4318.5.2 Using OptQuest1 on the Machine Interference Model 4398.5.3 Modeling Balking and Reneging 4438.6 Holding and Signaling Entities 4508.6.1 Redoing the M/M/1 Model with HOLD/SIGNAL 4518.7 Networks of Queueing Stations 4568.7.1 STATION, ROUTE, and SEQUENCE Modules 4618.8 Inventory Systems 4698.8.1 Modeling an (r;Q) Inventory Control Policy 4708.8.2 Modeling a MultiEchelonInventory System 4818.9 Summary 487Exercises 4899 Entity Movement and Material Handling 5079.1 Introduction 5079.2 Resource Constrained Transfer 5089.2.1 Implementing Resource Constrained Transfer 5119.2.2 Animating Resource Constrained Transfer 5189.3 Constrained Transfer with Transporters 5209.3.1 Test and Repair Shop with Workers as Transporters 5249.3.2 Animating Transporters 5299.4 Modeling Systems with Conveyors 5319.4.1 Test and Repair Shop with Conveyors 5369.4.2 Animating Conveyors 5419.4.3 Miscellaneous Issues in Conveyor Modeling 5439.5 Modeling Guided Path Transporters 5509.6 Summary 559Exercises 56010 Miscellaneous Topics in ArenaTM Modeling 56710.1 Introduction 56710.2 Non-stationary Processes 56810.2.1 Thinning Method 57210.2.2 Rate Inversion Method 57210.3 Advanced Resource Modeling 57610.3.1 Scheduled Capacity Changes 57710.3.2 Calculating Utilization 58510.3.3 Resource Failure Modeling 58810.4 Tabulating Frequencies using the STATISTIC Module 59110.5 Resource and Entity Costing 59410.5.1 Resource Costing 59410.5.2 Entity Costing 59810.6 Miscellaneous Modeling Concepts 60210.6.1 Picking Between Stations 60310.6.2 Generic Station Modeling 60710.6.3 Picking up and Dropping Off Entities 61210.7 Programming Concepts within ArenaTM 62110.7.1 Using the Generated Access File 62110.7.2 Working with Files, Excel, and Access 62610.7.3 Using Visual Basic for Applications 63910.7.4 Generating Correlated Random Variates 65210.8 Summary 655Exercises 65611 Application of Simulation Modeling 66311.1 Introduction 66311.2 SM Testing Contest Problem Description 66511.3 Answering the Basic Modeling Questions 67111.4 Detailed Modeling 67611.4.1 Conveyor and Station Modeling 67611.4.2 Modeling Samples and the Test Cells 67911.4.3 Modeling Sample Holders and the Load/Unload Area 68511.4.4 Performance Measure Modeling 68811.4.5 Simulation Horizon and Run Parameters 69011.4.6 Preliminary Experimental Analysis 69311.5 Final Experimental Analysis and Results 69411.5.1 Using the Process Analyzer on the Problem 69511.5.2 Using OptQuest on the Problem 70111.5.3 Investigating the New Logic Alternative 70211.6 Sensitivity Analysis 70311.7 Completing the Project 70411.8 Some Final Thoughts 707Exercises 709A Common Distributions 717B Statistical Tables 725C Distributions, Operators, Functions in ArenaTM 731D Queueing Theory Formulas 735E Inventory Theory Formulas 739F Useful Equations 742G ArenaTM Panel Modules 743Index 749

"This is an ideal textbook for upper-undergraduate and graduate courses in modeling and simulation within statistics, mathematics, industrial and civil engineering, construction management, business, computer science, and other departments where simulation is practiced. The book is also an excellent reference for professionals interested in mathematical modeling, simulation, and Arena." (Zentralblatt Math, 2016)