Adam / Dogramaci Current Issues in Computer Simulation

1. Auflage 2014
ISBN: 978-1-4832-5803-4
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 312 Seiten, Web PDF

Current Issues in Computer Simulation is a collection of papers dealing with computer simulation languages, statistical aspects of simulation, linkage with optimization and analytical models, as well as theory and application of simulation methodology. Some papers explain the General Purpose Simulation System (GPSS), a programming package incorporating a language to simulate discrete systems; and the SIMSCRIPT, a general-purpose simulation language using English commands, for example, FORTRAN. Another simulation language is the General Activity Simulation Program (GASP), providing for an organizational structure to build models to simulate the dynamic performance of systems on a digital computer. Other papers discuss simulation models of real systems, including corporate simulation models, multistage consumer choice process, determination of maximum occupancy for hospital facilities, and the juvenile court system. Many computer simulations are statistical sampling experiments performed on a model of the system under investigation. Other papers discuss some of the variables involved in the statistical design and analysis of simulation experiments such as variance reduction techniques, generation of random variates, and experimental layout. For example, one application simulates inventory systems when many items are stocked in various locations. The collection is suitable for programmers, computer engineers, businessmen, hospital administrators, schools officials, and depositories of huge volumes of information or data.

Autoren/Hrsg.

Adam, Nabil R.

Dogramaci, Ali

Inhaltsverzeichnis

1;Front Cover;1
2;Current Issues in Computer Simulation;4
3;Copyright Page;5
4;Table of Contents;6
5;LIST OF CONTRIBUTORS;14
6;PREFACE;16
7;ACKNOWLEDGMENTS;18
8;PART I: COMPUTER SIMULATION LANGUAGES;22
8.1;Chapter 1. Issues in Simulation Languages: A Brief Overview;24
8.1.1;I. Introduction;24
8.1.2;II. Simulation Languages: Some Basic Characteristics;24
8.1.3;III. Simulation Languages: Some Research and Development Related Issues;28
8.1.4;IV. Summary;32
8.1.5;References;33
8.2;Chapter 2. The Design of the GPSS Language;36
8.2.1;I. Introduction;36
8.2.2;II. The Nature of the GPSS Language;37
8.2.3;III. GPSS Examples;38
8.2.4;IV. Origins of GPSS;40
8.2.5;V. Block Diagram Languages;41
8.2.6;VI. The GPSS Simulation Algorithm;43
8.2.7;VII. Conclusions;45
8.2.8;References;46
8.3;Chapter 3. Simscript: Past, Present, and Some Thoughts about the Future;48
8.3.1;I. The Simscript Languages;48
8.3.2;II. Basic Concepts;51
8.3.3;III. An Example;59
8.3.4;IV. Some Thoughts about the Future;63
8.3.5;References;80
8.4;Chapter 4. GASP: Present Status and Future Prospects;82
8.4.1;I. Introduction;82
8.4.2;II. Modeling Philosophy Embodied in GASP;82
8.4.3;III. GASP Organization for Continuous Modeling;83
8.4.4;IV. GASP Organization for Discrete Models;85
8.4.5;V. GASP Organizational Structure for Combined Simulation;86
8.4.6;VI. Applications;87
8.4.7;VII. Current Research and Developments;88
8.4.8;VIII. Discussion;89
8.4.9;References;90
8.5;Chapter 5. Comparison of Future Event Set Algorithms for Simulations of Closed Queueing Systems;92
8.5.1;I. Introduction;92
8.5.2;II. Algorithms Evaluated;93
8.5.3;III. Models;95
8.5.4;IV. Methodology;96
8.5.5;V. Results and Conclusions;97
8.5.6;References;102
8.6;Chapter 6. Model Representation in Discrete Event Simulation: Prospects for Developing Documentation Standards;104
8.6.1;I. The Issues;104
8.6.2;II. Previous Work in Simulation Model Representation;105
8.6.3;III. Conical Methodology: Rationale and Overview;110
8.6.4;IV. Simulation Model Specification and Documentation Language;114
8.6.5;V. Summary;116
8.6.6;References;117
9;PART II: SIMULATION APPLICATIONS;120
9.1;Chapter 7. Applications of Simulation;122
9.1.1;I. Introduction;122
9.1.2;II. Objectives of Simulation;123
9.1.3;III. Some Issues in Simulation Applications;125
9.1.4;References;128
9.2;Chapter 8. Corporate Simulation Models;132
9.2.1;I. Introduction;132
9.2.2;II. Optimization;133
9.2.3;III. Risk Analysis;135
9.2.4;IV. Production Planning Models;137
9.2.5;V. Computer Software;138
9.2.6;VI. Practical Problems;139
9.2.7;VII. Summary and Conclusions;140
9.2.8;Appendix: Elements of a Planning and Modeling System;141
9.2.9;References;144
9.3;Chapter 9. Microsimulation of a Multistage Consumer Choice Process;146
9.3.1;I. Introduction;146
9.3.2;II. The Choice Set (or Evoked Set) {k};148
9.3.3;III. The Preference Vector {Pik};149
9.3.4;IV. Shape of Market {Sk};152
9.3.5;V. The Two-Stage Dynamic System;153
9.3.6;VI. Conclusion;156
9.3.7;References;157
9.4;Chapter 10. The Use of Simulation in the Determination of Maximum Occupancy for Hospital Facilities;158
9.4.1;I. Introduction;158
9.4.2;II. Methodology;160
9.4.3;III. Results;175
9.4.4;IV. Summary;181
9.4.5;References;182
9.5;Chapter 11. Simulating the Behavioral Implications of a National Computer Research Network;186
9.5.1;I. Introduction;186
9.5.2;II. Network Organization;187
9.5.3;III. Project Overview;188
9.5.4;IV. The Simulation Model;190
9.5.5;V. Initial Simulation Experiments;197
9.5.6;VI. Gaming Session;198
9.5.7;VII. Summary;202
9.5.8;References;203
9.6;Chapter 12. The Juvenile Court System: A Simulation Approach;204
9.6.1;I. Introduction;204
9.6.2;II. Overall Models;204
9.6.3;III. Court Models;205
9.6.4;IV. The Juvenile Court Model (JCM);206
9.6.5;V. Findings;215
9.6.6;VI. Summary and Conclusions;217
9.6.7;References;217
10;PART III: SIMULATION: STATISTICAL ASPECTS AND LINKAGE TO ANALYTICAL MODELS;220
10.1;Chapter 13. Statistical and Analytical Models in Simulation;222
10.1.1;References;224
10.2;Chapter 14. On Simulating Inventory Systems Where Demand Is Backlogged;228
10.2.1;I. Introduction;228
10.2.2;II. Shifting the Inventory Distribution;231
10.2.3;III. Statistical Reliability;238
10.2.4;IV. Conclusion;242
10.2.5;Appendix-Counterexample;243
10.2.6;References;243
10.3;Chapter 15. On Using Simulation to Extend OR/MS Theory: The Symbiosis of Simulation and Analysis;244
10.3.1;I. Introduction;244
10.3.2;II. Building Theory with Analysis and Simulation;245
10.3.3;III. Examples of the Use of Simulation and Analysis Together;248
10.3.4;IV. Examples Where Simulation and Analysis Could Have Been Used Together;249
10.3.5;V. Generation of Exogenous Events;251
10.3.6;VI. Summary;253
10.3.7;References;254
10.4;Chapter 16. Designing Correlation Induction Strategies for Simulation Experiments;256
10.4.1;I. Background and Notation;256
10.4.2;II. Design Criteria;261
10.4.3;III. Results for Orthogonally Blockable Designs;262
10.4.4;IV. An Invariance Property;263
10.4.5;V. Designing Correlation Induction Strategies;264
10.4.6;VI. A Simple Application;268
10.4.7;VII. A More Interesting Application;273
10.4.8;VIII. Summary;275
10.4.9;References;276
10.5;Chapter 17. A Variance Reduction Technique That Increases Regeneration Frequency;278
10.5.1;I. Introduction;278
10.5.2;II. Derivation of the Modified Markov Chain;279
10.5.3;III. Numerical Discussion;285
10.5.4;IV. Conclusions;289
10.5.5;References;290
10.6;Chapter 18. Simulation of Bivariate Distributions with Given Marginal Distribution Functions;292
10.6.1;I. Introduction;292
10.6.2;II. Correlation Measures;293
10.6.3;III. The Normal Method;294
10.6.4;IV. The Uniform Method;296
10.6.5;V. Uniqueness of Generation Methods and Extensions;297
10.6.6;VI. An Example of Simulation;298
10.6.7;Appendix;299
10.6.8;References;302
11;AUTHOR INDEX;304
12;SUBJECT INDEX;310