Discrete Event Simulation is a process-oriented text/reference that utilizes an eleven-step model to represent the simulation process from problem formulation to implementation and documentation. The book presents the necessary level of detail required to fully develop a model that produces meaningful results and considers the tools necessary to interpret those results. Sufficient background information is provided so that the underlying concepts of simulation are understood. Major topics covered in Discrete Event Simulation include probability and distributional theory, statistical estimation and inference, the generation of random variates, verification and validation techniques, time management methods, experimental design, and programming language considerations. The book also examines distributed simulation and issues related to distributing the physical process over a network of tightly coupled processors. Topics covered in this area include deadlock, synchronization, rollback, event management, and communication processes. Fully worked examples and numerous practical exercises have been drawn from the engineering disciplines and computer science, although they have been structured so that they will be useful as well to other disciplines such as economics, business administration, and management science. The presentation of techniques and methods in Discrete Event Simulation make it an ideal text/reference for all practitioners of discrete event simulation.

"This is an excellent and well-written text on discrete event simulation with a focus on applications in Operations Research. There is substantial attention to programming, output analysis, pseudo-random number generation and modelling and these sections are quite thorough. Methods are provided for generating pseudo-random numbers (including combining such streams) and for generating random numbers from most standard statistical distributions." --ISI Short Book Reviews, 22:2, August 2002

Considered by many authors as a technique for modelling stochastic, dynamic and discretely evolving systems, this technique has gained widespread acceptance among the practitioners who want to represent and improve complex systems. Since DES is a technique applied in incredibly different areas, this book reflects many different points of view about DES, thus, all authors describe how it is understood and applied within their context of work, providing an extensive understanding of what DES is. It can be said that the name of the book itself reflects the plurality that these points of view represent. The book embraces a number of topics covering theory, methods and applications to a wide range of sectors and problem areas that have been categorised into five groups. As well as the previously explained variety of points of view concerning DES, there is one additional thing to remark about this book: its richness when talking about actual data or actual data based analysis. When most academic areas are lacking application cases, roughly the half part of the chapters included in this book deal with actual problems or at least are based on actual data. Thus, the editor firmly believes that this book will be interesting for both beginners and practitioners in the area of DES.

The use of discrete-event simulation in various fields, such as in industry, logistics and public health, has really taken off over the last few decades. The implementation of discrete-event simulation does however require an understanding, and perhaps even a mastery, of precise theoretical and methodological principles. Discrete-Event Simulation presents the key concepts involved in any discrete-event simulation project, covering the most frequently used techniques for analysing data and results, the methodological and practical aspects of implementing discrete-event simulation, along with an introduction to the use of the “Arena” discrete-event simulation tool. This book combines the elements presented with applied examples, as well as numerous examples of simulation projects in various fields.

Complex artificial dynamic systems require advanced modeling techniques that can accommodate their asynchronous, concurrent, and highly non-linear nature. Discrete Event systems Specification (DEVS) provides a formal framework for hierarchical construction of discrete-event models in a modular manner, allowing for model re-use and reduced development time. Discrete Event Modeling and Simulation presents a practical approach focused on the creation of discrete-event applications. The book introduces the CD++ tool, an open-source framework that enables the simulation of discrete-event models. After setting up the basic theory of DEVS and Cell-DEVS, the author focuses on how to use the CD++ tool to define a variety of models in biology, physics, chemistry, and artificial systems. They also demonstrate how to map different modeling techniques, such as Finite State Machines and VHDL, to DEVS. The in-depth coverage elaborates on the creation of simulation software for DEVS models and the 3D visualization environments associated with these tools. A much-needed practical approach to creating discrete-event applications, this book offers world-class instruction on the field’s most useful modeling tools.

Concurrent simulation is over twenty years old. During that pe riod it has been widely adopted for the simulation of faults in digital circuits, for which it provides a combination of extreme efficiency and generality . Yet, it is remarkable that no book published so far presents a correct and sufficiently detailed treatment of concurrent simulation. A first reason to welcome into print the effort of the authors is, therefore, that it provides a much needed account of an important topic in design automation. This book is, however, unique for sev eral other reasons. It is safe to state that no individual has contrib uted more than Ernst Ulrich to the development of digital logic simulation. For concurrent simulation, one may say that Ernst has contributed more than the rest of the world. We would find such a claim difficult to dispute. The unique experience of the authors con fers a special character to this book: It is authoritative, inspired, and focused on what is conceptually important. Another unique aspect of this book, perhaps the one that will be the most surprising for many readers, is that it is strongly projected towards the future. Concurrent simulation is presented as a general experimentation methodology and new intriguing applications are analyzed. The discussion of multi-domain concurrent simulation-- recent work of Karen Panetta Lentz and Ernst Ulrich---is fascinat ing.

Discrete-event simulation has long been an integral part of the design process of complex engineering systems and the modelling of natural phenomena. Many of the systems that we seek to understand or control can be modelled as digital systems. In a digital model, we view the system at discrete instants of time, in effect taking snapshots of the system at these instants. For example, in a computer network simulation an event can be the sending of a message from one node to another node while in a VLSI logic simulation, the arrival of a signal at a gate may be viewed as an event. Digital systems such as computer systems are naturally susceptible to this approach. However, a variety of other systems may also be modelled this way. These include transportation systems such as air-traffic control systems, epidemiological models such as the spreading of a virus, and military war-gaming models. This book is representative of the advances in this field.

"This book provides a comprehensive overview of theory and practice in simulation systems focusing on major breakthroughs within the technological arena, with particular concentration on the accelerating principles, concepts and applications"--Provided by publisher.

This is the first book to make all the central concepts of discrete event simulation relevant for health technology assessment. Accessible to beginners, the book requires no prerequisites and describes the concepts with as little jargon as possible. It presents essential concepts, a fully worked out implementation example, approaches to analyze the simulations, the development of the required equations, model verification techniques, and validation. The book also covers various special topics and includes a real case study involving screening strategies for breast cancer surveillance.

Bringing together an international group of researchers involved in military, business, and health modeling and simulation, Conceptual Modeling for Discrete-Event Simulation presents a comprehensive view of the current state of the art in the field. The book addresses a host of issues, including: What is a conceptual model?How is conceptual modelin