From the Publisher:
This book presents a unified theory of Generalized Stochastic Petri Nets (GSPNs) together with a set of illustrative examples from different application fields. The continuing success of GSPNs and the increasing interest in using them as a modelling paradigm for the quantitative analysis of distributed systems suggested the preparation of this volume with the intent of providing newcomers to the field with a useful tool for their first approach. Readers will find a clear and informal explanation of the concepts followed by formal definitions when necessary or helpful. The largest section of the book however is devoted to showing how this methodology can be applied in a range of domains.

Modelling with Generalized Stochastic Petri Nets

This paper surveys verification and validation of models, especially simulation models in operations research. For verification it discusses 1) general good programming practice (such as modular programming), 2) checking intermediate simulation outputs through tracing and statistical testing per module, 3) statistical testing of final simulation outputs against analytical results, and 4) animation. For validation it discusses 1) obtaining real-worl data, 2) comparing simulated and real data through simple tests such as graphical, Schruben-Turing, and t tests, 3) testing whether simulated and real responses are positively correlated and moreover have the same mean, using two new statistical procedures based on regression analysis, 4) sensitivity analysis based on design of experiments and regression analysis, and risk or uncertainty analysis based on Monte Carlo sampling, and 5) white versus black box simulation models. Both verification and validation require good documentation, and are crucial parts of assessment, credibility, and accreditation. A bibliography with 61 references is included.

Verification and validation of simulation models

Advances in scientific computing have made modelling and simulation an important part of the decision-making process in engineering, science, and public policy. This book provides a comprehensive and systematic development of the basic concepts, principles, and procedures for verification and validation of models and simulations. The emphasis is placed on models that are described by partial differential and integral equations and the simulations that result from their numerical solution. The methods described can be applied to a wide range of technical fields, from the physical sciences, engineering and technology and industry, through to environmental regulations and safety, product and plant safety, financial investing, and governmental regulations. This book will be genuinely welcomed by researchers, practitioners, and decision makers in a broad range of fields, who seek to improve the credibility and reliability of simulation results. It will also be appropriate either for university courses or for independent study.

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Verification and Validation in Scientific Computing

Objects. The ~ b s t rac t ~ b j ect forms the fundamental base class for the entire design and all other classes are derived from this base class. The Abstract Object class defines and characterizes all the essential properties every class in this 404 OBJECT-ORIENTED SIMULATION

Handbook of Simulation

From the Publisher:
This book,written by the creators of SIMAN,provides an introduction to simulation modeling using the SIMAN simulation language. Basic modeling concepts and various simulation methodologies are discussed to highlight practical applications of simulation and SIMAN. The second edition has been updated to included the latest version of this simulation program,including the Cinema platform and Arena.

C. Dennis Pegden

Papers

Introduction to Simulation Using Siman