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This graduate-level textbook covers modelling, programming and analysis of stochastic computer simulation experiments, including the mathematical and statistical foundations of simulation and why it works.
This book covers modeling, programming and analysis of simulation experiments and offers a rigorous treatment of the foundations of simulation and why it works. Emphasizes lasting principles, includes end of chapter exercises and an online manual of solutions.
For junior- and senior-level simulation courses in engineering, business, or computer science.While most books on simulation focus on particular software tools, Discrete Event System Simulation examines the principles of modeling and analysis that translate to all such tools. This language-independent text explains the basic aspects of the technology, including the proper collection and analysis of data, the use of analytic techniques, verification and validation of models, and designing simulation experiments. It offers an up-to-date treatment of simulation of manufacturing and material handling systems, computer systems, and computer networks. Students and instructors will find a variety of resources at the associated website, www.bcnn.net/, including simulation source code for download, additional exercises and solutions, web links and errata.
A collection of chapters on key issues in the design and analysis of computer simulation experiments on models of stochastic systems. It focuses on design and analysis issues and intends to survey the concepts, principles, tools and techniques that underlie the theory and practice of stochastic simulation design and analysis.
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