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100	1		_aSengupta, Sankar.
245	1	0	_aSystem Simulation and Modeling.
250			_a1st ed.
300			_a1 online resource (264 pages)
505	0		_aCover -- Contents -- Preface -- Chapter 1: Introduction to Simulation -- 1.1 Introduction to Simulation -- 1.2 How Would You Decide if Simulation Is the Right Tool? -- 1.3 Areas of Application -- 1.4 Advantages and Disadvantages of Simulation -- 1.5 Types of Simulation Model -- 1.5.1 Static vs. Dynamic Model -- 1.5.2 Deterministic Vs. Stochastic Model -- 1.5.3 Continuous vs. Discrete Model -- 1.6 Major Steps of a Simulation Study -- 1.7 System Dynamics Model -- 1.7.1 Problem Statement (Box Design) -- 1.7.2 Problem Statement (Network System Analysis) -- 1.7.3 Problem Statement (Investment Model) -- 1.7.4 Problem Statement (Radio-active Decay) -- 1.7.5 Problem Statement (Predator-Prey - A Continuous Simulation Model) -- 1.7.6 Problem Statement (Refinance a House Mortgage) -- 1.7.7 Problem Statement (Petri-net Model) -- 1.7.8 Problem Statement (Regression Model) -- Summary -- Exercises -- Chapter 2: Review of Probability and Statistics -- 2.1 Discrete Random Variable -- 2.2 Continuous Random Variable -- 2.3 Descriptive Characteristics of a Distribution -- 2.3.1 Mean and Variance -- 2.3.2 Moment About Origin -- 2.3.3 Moment About Mean -- 2.3.4 Measure of Dependence -- 2.4 Test of Hypothesis and Estimation of Confidence Interval -- 2.4.1 Testing of Hypothesis -- 2.4.2 Confidence Interval -- 2.5 Estimation Error -- 2.6 Estimation of Parameters -- 2.6.1 Point Estimate of a Parameter -- 2.6.2 Method of Maximum Likelihood Estimation (MLE) -- 2.7 Goodness-of-fit Tests -- 2.7.1 Chi-square Test -- 2.7.2 K-S Test -- 2.7.3 Comparison Between Chi-Square Test and K-S Test -- 2.7.4 Paired t-Test -- Summary -- Exercises -- Chapter 3: Managing the Event Calendar in a Discreteevent Simulation Model -- 3.1 Time Advance Methods -- 3.1.1 Fixed Increment Time Advance -- 3.1.2 Next-event Time Advance -- 3.2 Data Collection -- Summary -- Exercises.
505	8		_aChapter 4: Modeling Input Data -- 4.1 Input Modeling Steps -- 4.2 Arena Input Analyzer -- 4.3 Selection of the Best Distribution -- 4.4 Discrete Distribution -- 4.5 Empirical Distribution -- 4.6 Distribution Parameters -- 4.7 Beware of Multiple Choices -- Summary -- Exercises -- Chapter 5: Generation of Random Numbers -- 5.1 Generating Random Numbers -- 5.1.1 Linear Congruential Method (LCG) -- 5.1.2 A Degenerate Random Number Generator -- 5.2 Lagged Fibonacci Generators (LFG) -- 5.3 Combination Generators -- 5.4 The New RNG Used in Arena -- 5.5 Some Popular Generators -- 5.6 Statistical Tests for a Random Number Generator -- 5.6.1 Frequency Tests -- Summary -- Exercises -- Chapter 6: Generation of Random Variates -- 6.1 Inverse Transform Method -- 6.1.1 Example - Uniform Distribution U(a, b) -- 6.1.2 Example - A Discrete Distribution -- 6.1.3 Example - Exponential Distribution -- 6.1.4 Example - Normal Distribution -- 6.1.5 Example - Triangular Distribution -- 6.1.6 Example - Bernoulli Distribution -- 6.1.7 Example - Binomial Distribution -- 6.1.8 Example - Poisson Distribution -- 6.1.9 Example - Weibull Distribution -- 6.2 Method of Convolution -- 6.2.1 m-Erlang Distribution -- 6.3 Acceptance-Rejection Method -- 6.3.1 Example -- 6.4 Special Properties -- 6.5 Empirical Distribution -- Summary -- Exercises -- Chapter 7: Generic Features and Introduction to Arena -- 7.1 Generic Features of Discrete-event Simulation Software -- 7.2 Introduction to Arena -- 7.2.1 Basic Process Modules -- 7.2.2 Data Modules -- 7.2.3 Run Set-up Module -- Summary -- Exercises -- Chapter 8: Real World Applications of Simulation -- 8.1 Transfer Line Model -- 8.1.1 Simulation Model -- 8.2 Inventory System Model -- 8.3 Deadlock Detection Model -- 8.4 Computer Center Model -- 8.5 Job Shop Model -- 8.6 Just-in-time Model -- 8.7 Pi value Estimation -- 8.8 Capital Recovery Problem.
505	8		_a8.9 Economics of Insurance Policy -- 8.10 Reliability Estimation -- 8.11 Warranty Problem (Application on Markov's Chain) -- 8.12 Interpretation of Confidence Interval of a Parameter -- 8.13 Computer Network Model -- Summary -- Exercises -- Chapter 9: Discrete-Continuous Simulation -- 9.1 Problem Statement -- Summary -- Exercises -- Chapter 10: Verification and Validation of Simulation Models -- Summary -- Exercises -- Chapter 11: Introduction to Queuing System -- 11.1 Queuing System Nomenclature -- 11.2 Markovian Queuing Systems -- 11.2.1 M/M/1/GD/∞/∞ System -- 11.2.2 M/M/1/GD/N/∞ System -- 11.2.3 Multiple Servers, Infinite System Capacity - M/M/c/GD/∞/∞ System -- 11.2.4 Multiple Parallel Servers with Finite System Capacity -M/M/c/GD/N/∞ System -- 11.2.5 Machine Repair Model - M/M/R/GD/N/N System -- 11.3 Solved Examples -- 11.3.5 Machine Repair Problem -- 11.3.6 Self-serve Model (M/M/∞/GD/∞/∞ Model) -- 11.4 M/G/1/GD/∞/∞ System (Non-Markovian Queue) -- 11.4.1 Numerical Example -- 11.5 Analytical Model vs. Simulation Model -- Summary -- Exercises -- Chapter 12: Output Analysis -- 12.1 Terminating System -- 12.2 Non-terminating System -- 12.2.1 Problem Statement - Terminating System -- 12.2.2 Restaurant Management Simulation Model -- 12.2.3 Determination of Number of Replications -- 12.2.4 Problem Statement for a Non-terminating System -- 12.2.5 Output Analysis -- 12.2.6 Alternate Method -- 12.3 Variance Reduction Techniques -- 12.3.1 Classification of VRTs -- Summary -- Exercises -- Chapter 13: Agent-based Simulation -- 13.1 John Conway's Game "Life" -- 13.2 Characteristics of the Consumer Behavior Model -- 13.3 Simulation Model -- 13.4 Result -- 13.5 Agent-based Simulation Model for Spread of Disease -- 13.5.1 Model Characteristics -- 13.5.2 Model Description -- Summary -- Exercises -- Chapter 14: Simulation and Optimization.
505	8		_a14.1 Buffer Size Optimization Model -- 14.1.1 OptQuest Outputs -- 14.2 Inventory System Optimization Model (Problem Statement) -- 14.2.1 OptQuest Outputs -- Summary -- Exercises -- Chapter 15: Simulation Software Review -- 15.1 Arena Software -- 15.1.1 Intended Audience -- 15.1.2 Commercial Software Editions -- 15.1.3 Academic Software Editions -- 15.2 The ProModel Optimization Suite -- 15.2.1 The ProModel Methodology -- 15.2.2 The ProModel Advantage -- 15.2.3 ProModel Features -- 15.3 SIMUL8 Standard Simulation Software -- 15.3.1 Overview -- 15.3.2 Model Building -- 15.4 WITNESS Overview -- 15.4.1 Key Benefits of WITNESS -- 15.4.2 WITNESS Optimizer -- 15.4.3 WITNESS VR -- 15.5 Simulation Using GPSS/H -- 15.5.1 GPSS/H Overview -- 15.5.2 Important Features of GPSS/H -- 15.6 Quest Software -- 15.6.1 Benefits of Using Quest -- 15.6.2 Problems with Quest -- References -- Index.
520			_aComputer simulation is an attempt to model a real-life or hypothetical situation on a computer so that it can be studied to see how the system works. This book provides an excellent coverage on system modeling and simulation with the help of examples and applications taken from diverse areas like computer systems, statistics, manufacturing and insurance. The book presents valuable guidelines on the materials required to build a simulation model, explains the process of evaluating results and helps to take decisions based on the results. Apart from an in-depth discussion on Arena and its step-by-step approach to convert a problem statement into an Arena simulation model, the book also briefly discusses a number of commercially available software on simulation like GPSS, SIMSCRIPT and DYNAMO.
590			_aElectronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2018. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
655		4	_aElectronic books.
776	0	8	_iPrint version: _aSengupta, Sankar _tSystem Simulation and Modeling _d : Pearson India,c2013
797	2		_aProQuest (Firm)
856	4	0	_uhttps://ebookcentral.proquest.com/lib/cethalassery/detail.action?docID=5125336 _zClick to View
942			_2ddc _cBK