Theory of Modeling and Simulation
Theory of Modeling and Simulation

Author: Bernard P. Zeigler

Publisher: Academic Press

Published: 2018-08-14

Total Pages: 694

ISBN-13: 0128134070

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Theory of Modeling and Simulation: Discrete Event & Iterative System Computational Foundations, Third Edition, continues the legacy of this authoritative and complete theoretical work. It is ideal for graduate and PhD students and working engineers interested in posing and solving problems using the tools of logico-mathematical modeling and computer simulation. Continuing its emphasis on the integration of discrete event and continuous modeling approaches, the work focuses light on DEVS and its potential to support the co-existence and interoperation of multiple formalisms in model components. New sections in this updated edition include discussions on important new extensions to theory, including chapter-length coverage of iterative system specification and DEVS and their fundamental importance, closure under coupling for iteratively specified systems, existence, uniqueness, non-deterministic conditions, and temporal progressiveness (legitimacy). Presents a 40% revised and expanded new edition of this classic book with many important post-2000 extensions to core theory Provides a streamlined introduction to Discrete Event System Specification (DEVS) formalism for modeling and simulation Packages all the "need-to-know" information on DEVS formalism in one place Expanded to include an online ancillary package, including numerous examples of theory and implementation in DEVS-based software, student solutions and instructors manual

An Introduction to the Regenerative Method for Simulation Analysis
An Introduction to the Regenerative Method for Simulation Analysis

Author: M. A. Crane

Publisher: Springer

Published: 1977

Total Pages: 126

ISBN-13:

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The purpose of this report is to provide an introduction to the regenerative method for simulation analysis. The simulations are simulations of stochastic systems, i.e., systems with random elements. The regenerative approach leads to a statistical methodology for analyzing the output of those simulations which have the property of 'starting afresh probabilistically' from time to time. The class of such simulations is very large and very important, including simulations of a broad variety of queues and queueing networks, inventory systems, inspection, maintenance, and repair operations, and numerous other situations.

Complexity and Information
Complexity and Information

Author: J. F. Traub

Publisher: Cambridge University Press

Published: 1998-12-10

Total Pages: 152

ISBN-13: 9780521485067

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The twin themes of computational complexity and information pervade this 1998 book. It starts with an introduction to the computational complexity of continuous mathematical models, that is, information-based complexity. This is then used to illustrate a variety of topics, including breaking the curse of dimensionality, complexity of path integration, solvability of ill-posed problems, the value of information in computation, assigning values to mathematical hypotheses, and new, improved methods for mathematical finance. The style is informal, and the goals are exposition, insight and motivation. A comprehensive bibliography is provided, to which readers are referred for precise statements of results and their proofs. As the first introductory book on the subject it will be invaluable as a guide to the area for the many students and researchers whose disciplines, ranging from physics to finance, are influenced by the computational complexity of continuous problems.

Handbook of Simulation Optimization
Handbook of Simulation Optimization

Author: Michael C Fu

Publisher: Springer

Published: 2014-11-13

Total Pages: 400

ISBN-13: 1493913840

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The Handbook of Simulation Optimization presents an overview of the state of the art of simulation optimization, providing a survey of the most well-established approaches for optimizing stochastic simulation models and a sampling of recent research advances in theory and methodology. Leading contributors cover such topics as discrete optimization via simulation, ranking and selection, efficient simulation budget allocation, random search methods, response surface methodology, stochastic gradient estimation, stochastic approximation, sample average approximation, stochastic constraints, variance reduction techniques, model-based stochastic search methods and Markov decision processes. This single volume should serve as a reference for those already in the field and as a means for those new to the field for understanding and applying the main approaches. The intended audience includes researchers, practitioners and graduate students in the business/engineering fields of operations research, management science, operations management and stochastic control, as well as in economics/finance and computer science.

Building Software for Simulation
Building Software for Simulation

Author: James J. Nutaro

Publisher: John Wiley & Sons

Published: 2011-03-23

Total Pages: 372

ISBN-13: 1118099451

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Building Software for Simulation A unique guide to the design and implementation of simulation software This book offers a concise introduction to the art of building simulation software, collecting the most important concepts and algorithms in one place. Written for both individuals new to the field of modeling and simulation as well as experienced practitioners, this guide explains the design and implementation of simulation software used in the engineering of large systems while presenting the relevant mathematical elements, concept discussions, and code development. The book approaches the topic from the perspective of Zeigler’s theory of modeling and simulation, introducing the theory’s fundamental concepts and showing how to apply them to engineering problems. Readers will learn five necessary skills for building simulations of complicated systems: Working with fundamental abstractions for simulating dynamic systems Developing basic simulation algorithms for continuous and discrete event models Combining continuous and discrete event simulations into a coherent whole Applying strategies for testing a simulation Understanding the theoretical foundations of the modeling constructs and simulation algorithms The central chapters of the book introduce, explain, and demonstrate the elements of the theory that are most important for building simulation tools. They are bracketed by applications to robotics, control and communications, and electric power systems; these comprehensive examples clearly illustrate how the concepts and algorithms are put to use. Readers will explore the design of object-oriented simulation programs, simulation using multi-core processors, and the integration of simulators into larger software systems. The focus on software makes this book particularly useful for computer science and computer engineering courses in simulation that focus on building simulators. It is indispensable reading for undergraduate and graduate students studying modeling and simulation, as well as for practicing scientists and engineers involved in the development of simulation tools.