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Simulation modeling and analysis

Author: Averill M Law
Publisher: New York, NY : McGraw-Hill Education, [2015] ©2015
Edition/Format:   Print book : English : Fifth editionView all editions and formats
Summary:

Provides a comprehensive and technically correct treatment of all important aspects of a simulation study. This book strives to make this material understandable by the use of intuition and numerous  Read more...

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Document Type: Book
All Authors / Contributors: Averill M Law
ISBN: 9780073401324 0073401323
OCLC Number: 893707440
Description: 776 pages, 4 unnumbered pages of plates : color illustrations ; 25 cm
Contents: Note continued: 11.4. Control Variates --
11.5. Indirect Estimation --
11.6. Conditioning --
Problems --
12.1. Introduction --
12.2. 2k Factorial Designs --
12.3. 2k-P Fractional Factorial Designs --
12.4. Response Surfaces and Metamodels --
12.4.1. Introduction and Analysis of the Inventory Model --
12.4.2. Analysis of the Predator-Prey Model --
12.4.3. Space-Filling Designs and Kriging --
12.5. Simulation-Based Optimization --
12.5.1. Optimum-Seeking Methods --
12.5.2. Optimum-Seeking Packages Interfaced with Simulation Software --
Problems --
13.1. Introduction --
13.2. Agent-Based Simulation --
13.2.1. Detailed Examples --
13.2.2. Time-Advance Mechanisms for ABS --
13.2.3. Summary of ABS --
13.3. Continuous Simulation --
13.3.1. System Dynamics --
13.4. Combined Discrete-Continuous Simulation --
13.5. Monte Carlo Simulation --
13.6. Spreadsheet Simulation --
Problems. Machine generated contents note: 1.1. Nature of Simulation --
1.2. Systems, Models, and Simulation --
1.3. Discrete-Event Simulation --
1.3.1. Time-Advance Mechanisms --
1.3.2. Components and Organization of a Discrete-Event Simulation Model --
1.4. Simulation of a Single-Server Queueing System --
1.4.1. Problem Statement --
1.4.2. Intuitive Explanation --
1.4.3. Program Organization and Logic --
1.4.4. C Program --
1.4.5. Simulation Output and Discussion --
1.4.6. Alternative Stopping Rules --
1.4.7. Determining the Events and Variables --
1.5. Simulation of an Inventory System --
1.5.1. Problem Statement --
1.5.2. Program Organization and Logic --
1.5.3. C Program --
1.5.4. Simulation Output and Discussion --
1.6. Parallel/Distributed Simulation and the High Level Architecture --
1.6.1. Parallel Simulation --
1.6.2. Distributed Simulation and the High Level Architecture --
1.7. Steps in a Sound Simulation Study --
1.8. Advantages, Disadvantages, and Pitfalls of Simulation --
Appendix 1A: Fixed-Increment Time Advance --
Appendix 1B: A Primer on Queueing Systems --
1B.1. Components of a Queueing System --
1B.2. Notation for Queueing Systems --
1B.3. Measures of Performance for Queueing Systems --
Problems --
2.1. Introduction --
2.2. List Processing in Simulation --
2.2.1. Approaches to Storing Lists in a Computer --
2.2.2. Linked Storage Allocation --
2.3. Simple Simulation Language: simlib --
2.4. Single-Server Queueing Simulation with simlib --
2.4.1. Problem Statement --
2.4.2. simlib Program --
2.4.3. Simulation Output and Discussion --
2.5. Time-Shared Computer Model --
2.5.1. Problem Statement --
2.5.2. simlib Program --
2.5.3. Simulation Output and Discussion --
2.6. Multiteller Bank with Jockeying --
2.6.1. Problem Statement --
2.6.2. simlib Program --
2.6.3. Simulation Output and Discussion --
2.7. Job-Shop Model --
2.7.1. Problem Statement --
2.7.2. simlib Program --
2.7.3. Simulation Output and Discussion --
2.8. Efficient Event-List Management --
Appendix 2A: C Code for simlib --
Problems --
3.1. Introduction --
3.2. Comparison of Simulation Packages with Programming Languages --
3.3. Classification of Simulation Software --
3.3.1. General-Purpose vs. Application-Oriented Simulation Packages --
3.3.2. Modeling Approaches --
3.3.3. Common Modeling Elements --
3.4. Desirable Software Features --
3.4.1. General Capabilities --
3.4.2. Hardware and Software Requirements --
3.4.3. Animation and Dynamic Graphics --
3.4.4. Statistical Capabilities --
3.4.5. Customer Support and Documentation --
3.4.6. Output Reports and Graphics --
3.5. General-Purpose Simulation Packages --
3.5.1. Arena --
3.5.2. ExtendSim --
3.5.3. Simio --
3.5.4. Other General-Purpose Simulation Packages --
3.6. Object-Oriented Simulation --
3.7. Examples of Application-Oriented Simulation Packages --
4.1. Introduction --
4.2. Random Variables and Their Properties --
4.3. Simulation Output Data and Stochastic Processes --
4.4. Estimation of Means, Variances, and Correlations --
4.5. Confidence Intervals and Hypothesis Tests for the Mean --
4.6. Strong Law of Large Numbers --
4.7. Danger of Replacing a Probability Distribution by its Mean --
Appendix 4A: Comments on Covariance-Stationary Processes --
Problems --
5.1. Introduction and Definitions --
5.2. Guidelines for Determining the Level of Model Detail --
5.3. Verification of Simulation Computer Programs --
5.4. Techniques for Increasing Model Validity and Credibility --
5.4.1. Collect High-Quality Information and Data on the System --
5.4.2. Interact with the Manager on a Regular Basis --
5.4.3. Maintain a Written Assumptions Document and Perform a Structured Walk-Through --
5.4.4. Validate Components of the Model by Using Quantitative Techniques --
5.4.5. Validate the Output from the Overall Simulation Model --
5.4.6. Animation --
5.5. Management's Role in the Simulation Process --
5.6. Statistical Procedures for Comparing Real-World Observations and Simulation Output Data --
5.6.1. Inspection Approach --
5.6.2. Confidence-Interval Approach Based on Independent Data --
5.6.3. Time-Series Approaches --
5.6.4. Other Approaches --
Problems --
6.1. Introduction --
6.2. Useful Probability Distributions --
6.2.1. Parameterization of Continuous Distributions --
6.2.2. Continuous Distributions --
6.2.3. Discrete Distributions --
6.2.4. Empirical Distributions --
6.3. Techniques for Assessing Sample Independence --
6.4. Activity I: Hypothesizing Families of Distributions --
6.4.1. Summary Statistics --
6.4.2. Histograms --
6.4.3. Quantile Summaries and Box Plots --
6.5. Activity II: Estimation of Parameters --
6.6. Activity III: Determining How Representative the Fitted Distributions Are --
6.6.1. Heuristic Procedures --
6.6.2. Goodness-of-Fit Tests --
6.7. ExpertFit Software and an Extended Example --
6.8. Shifted and Truncated Distributions --
6.9. Bezier Distributions --
6.10. Specifying Multivariate Distributions, Correlations, and Stochastic Processes --
6.10.1. Specifying Multivariate Distributions --
6.10.2. Specifying Arbitrary Marginal Distributions and Correlations --
6.10.3. Specifying Stochastic Processes --
6.11. Selecting a Distribution in the Absence of Data --
6.12. Models of Arrival Processes --
6.12.1. Poisson Processes --
6.12.2. Nonstationary Poisson Processes --
6.12.3. Batch Arrivals --
6.13. Assessing the Homogeneity of Different Data Sets --
Appendix 6A: Tables of MLEs for the Gamma and Beta Distributions --
Problems --
7.1. Introduction --
7.2. Linear Congruential Generators --
7.2.1. Mixed Generators --
7.2.2. Multiplicative Generators --
7.3. Other Kinds of Generators --
7.3.1. More General Congruences --
7.3.2. Composite Generators --
7.3.3. Feedback Shift Register Generators --
7.4. Testing Random-Number Generators --
7.4.1. Empirical Tests --
7.4.2. Theoretical Tests --
7.4.3. Some General Observations on Testing --
Appendix 7A: Portable C Code for a PMMLCG --
Appendix 7B: Portable C Code for a Combined MRG --
Problems --
8.1. Introduction --
8.2. General Approaches to Generating Random Variates --
8.2.1. Inverse Transform --
8.2.2. Composition --
8.2.3. Convolution --
8.2.4. Acceptance-Rejection --
8.2.5. Ratio of Uniforms --
8.2.6. Special Properties --
8.3. Generating Continuous Random Variates --
8.3.1. Uniform --
8.3.2. Exponential --
8.3.3. m-Erlang --
8.3.4. Gamma --
8.3.5. Weibull --
8.3.6. Normal --
8.3.7. Lognormal --
8.3.8. Beta --
8.3.9. Pearson Type V --
8.3.10. Pearson Type VI --
8.3.11. Log-Logistic --
8.3.12. Johnson Bounded --
8.3.13. Johnson Unbounded --
8.3.14. Bézier --
8.3.15. Triangular --
8.3.16. Empirical Distributions --
8.4. Generating Discrete Random Variates --
8.4.1. Bernoulli --
8.4.2. Discrete Uniform --
8.4.3. Arbitrary Discrete Distribution --
8.4.4. Binomial --
8.4.5. Geometric --
8.4.6. Negative Binomial --
8.4.7. Poisson --
8.5. Generating Random Vectors, Correlated Random Variates, and Stochastic Processes --
8.5.1. Using Conditional Distributions --
8.5.2. Multivariate Normal and Multivariate Lognormal --
8.5.3. Correlated Gamma Random Variates --
8.5.4. Generating from Multivariate Families --
8.5.5. Generating Random Vectors with Arbitrarily Specified Marginal Distributions and Correlations --
8.5.6. Generating Stochastic Processes --
8.6. Generating Arrival Processes --
8.6.1. Poisson Processes --
8.6.2. Nonstationary Poisson Processes --
8.6.3. Batch Arrivals --
Appendix 8A: Validity of the Acceptance-Rejection Method --
Appendix 8B: Setup for the Alias Method --
Problems --
9.1. Introduction --
9.2. Transient and Steady-State Behavior of a Stochastic Process --
9.3. Types of Simulations with Regard to Output Analysis --
9.4. Statistical Analysis for Terminating Simulations --
9.4.1. Estimating Means --
9.4.2. Estimating Other Measures of Performance --
9.4.3. Choosing Initial Conditions --
9.5. Statistical Analysis for Steady-State Parameters --
9.5.1. Problem of the Initial Transient --
9.5.2. Replication/Deletion Approach for Means --
9.5.3. Other Approaches for Means --
9.5.4. Estimating Other Measures of Performance --
9.6. Statistical Analysis for Steady-State Cycle Parameters --
9.7. Multiple Measures of Performance --
9.8. Time Plots of Important Variables --
Appendix 9A: Ratios of Expectations and Jackknife Estimators --
Problems --
10.1. Introduction --
10.2. Confidence Intervals for the Difference between the Expected Responses of Two Systems --
10.2.1. Paired-t Confidence Interval --
10.2.2. Modified Two-Sample-t Confidence Interval --
10.2.3. Contrasting the Two Methods --
10.2.4. Comparisons Based on Steady-State Measures of Performance --
10.3. Confidence Intervals for Comparing More than Two Systems --
10.3.1. Comparisons with a Standard --
10.3.2. All Pairwise Comparisons --
10.3.3. Multiple Comparisons with the Best --
10.4. Ranking and Selection --
10.4.1. Selecting the Best of k Systems --
10.4.2. Selecting a Subset of Size m Containing the Best of k Systems --
10.4.3. Additional --
Problems and Methods --
Appendix 10A: Validity of the Selection Procedures --
Appendix 10B: Constants for the Selection Procedures --
Problems --
11.1. Introduction --
11.2. Common Random Numbers --
11.2.1. Rationale --
11.2.2. Applicability --
11.2.3. Synchronization --
11.2.4. Some Examples --
11.3. Antithetic Variates.
Responsibility: Averill M. Law, President Averill M. Law & Associates, Inc. Tucson, Arizona, USA, www.averill-law.com.

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