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Since the publication of the first edition in 1982, the goal of Simulation Modeling and Analysis has always been to provide a comprehensive, state-of-the-art, and technically correct treatment of all important aspects of a simulation study. The book strives to make this material understandable by the use of intuition and numerous figures, examples, and problems. It is equally well suited for use in university courses, simulation practice, and self study. The book is widely regarded as the “bible” of simulation and now has more than 100,000 copies in print. The book can serve as the primary text for a variety of courses; for example: • A first course in simulation at the junior, senior, or beginning-graduate-student level in engineering, manufacturing, business, or computer science (Chaps. 1 through 4, and parts of Chaps. 5 through 9). At the end of such a course, the students will be prepared to carry out complete and effective simulation studies, and to take advanced simulation courses. • A second course in simulation for graduate students in any of the above disciplines (most of Chaps. 5 through 12). After completing this course, the student should be familiar with the more advanced methodological issues involved in a simulation study, and should be prepared to understand and conduct simulation research. • An introduction to simulation as part of a general course in operations research or management science (part of Chaps. 1, 3, 5, 6, and 9).
Simulation Modeling and Analysis with Arena is a highly readable textbook which treats the essentials of the Monte Carlo discrete-event simulation methodology, and does so in the context of a popular Arena simulation environment. It treats simulation modeling as an in-vitro laboratory that facilitates the understanding of complex systems and experimentation with what-if scenarios in order to estimate their performance metrics. The book contains chapters on the simulation modeling methodology and the underpinnings of discrete-event systems, as well as the relevant underlying probability, statistics, stochastic processes, input analysis, model validation and output analysis. All simulation-related concepts are illustrated in numerous Arena examples, encompassing production lines, manufacturing and inventory systems, transportation systems, and computer information systems in networked settings. - Introduces the concept of discrete event Monte Carlo simulation, the most commonly used methodology for modeling and analysis of complex systems - Covers essential workings of the popular animated simulation language, ARENA, including set-up, design parameters, input data, and output analysis, along with a wide variety of sample model applications from production lines to transportation systems - Reviews elements of statistics, probability, and stochastic processes relevant to simulation modeling
Emphasizes a hands-on approach to learning statistical analysis and model building through the use of comprehensive examples, problems sets, and software applications With a unique blend of theory and applications, Simulation Modeling and Arena®, Second Edition integrates coverage of statistical analysis and model building to emphasize the importance of both topics in simulation. Featuring introductory coverage on how simulation works and why it matters, the Second Edition expands coverage on static simulation and the applications of spreadsheets to perform simulation. The new edition also introduces the use of the open source statistical package, R, for both performing statistical testing and fitting distributions. In addition, the models are presented in a clear and precise pseudo-code form, which aids in understanding and model communication. Simulation Modeling and Arena, Second Edition also features: Updated coverage of necessary statistical modeling concepts such as confidence interval construction, hypothesis testing, and parameter estimation Additional examples of the simulation clock within discrete event simulation modeling involving the mechanics of time advancement by hand simulation A guide to the Arena Run Controller, which features a debugging scenario New homework problems that cover a wider range of engineering applications in transportation, logistics, healthcare, and computer science A related website with an Instructor’s Solutions Manual, PowerPoint® slides, test bank questions, and data sets for each chapter Simulation Modeling and Arena, Second Edition is an ideal textbook for upper-undergraduate and graduate courses in modeling and simulation within statistics, mathematics, industrial and civil engineering, construction management, business, computer science, and other departments where simulation is practiced. The book is also an excellent reference for professionals interested in mathematical modeling, simulation, and Arena.
Recently there has been considerable interest in qualitative methods in simulation and mathematical model- ing. Qualitative Simulation Modeling and Analysis is the first book to thoroughly review fundamental concepts in the field of qualitative simulation. The book will appeal to readers in a variety of disciplines including researchers in simulation methodology, artificial intelligence and engineering. This book boldly attempts to bring together, for the first time, the qualitative techniques previously found only in hard-to-find journals dedicated to single disciplines. The book is written for scientists and engineers interested in improving their knowledge of simulation modeling. The "qualitative" nature of the book stresses concepts of invariance, uncertainty and graph-theoretic bases for modeling and analysis.
"This book opens up the world of simulation to you by providing the basics of general simulation techonology, identifying the skills needed for successful simulation projects, and introducting a state-of-the-art simulation package." --
"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
Coherent introduction to techniques also offers a guide to the mathematical, numerical, and simulation tools of systems analysis. Includes formulation of models, analysis, and interpretation of results. 1995 edition.
one-of-a-kind introduction to the theory and application of modeling and simulation techniques in the realm of international studies Modeling and Simulation for Analyzing Global Events provides an orientation to the theory and application of modeling and simulation techniques in social science disciplines. This book guides readers in developing quantitative and numeric representations of real-world events based on qualitative analysis. With an emphasis on gathering and mapping empirical data, the authors detail the steps needed for accurately analyzing global events and outline the selection and construction of the best model for understanding the event¿s data. Providing a theoretical foundation while also illustrating modern examples, the book contains three parts: Advancing Global Studies—introduces the what, when, and why of modeling and simulation and also explores its brief history, various uses, and some of the advantages and disadvantages of modeling and simulation in problem solving. In addition, the differences in qualitative and quantitative research methods, mapping data, and conducting model validation are also discussed. Modeling Paradigms—examines various methods of modeling including system dynamics, agent-based modeling, social network modeling, and game theory. This section also explores the theory and construction of these modeling paradigms, the fundamentals for their application, and various contexts for their use. Modeling Global Events—applies the modeling paradigms to four real-world events that are representative of several fundamental areas of social science studies: internal commotion within an anarchic state, a multi-layered study of the Solidarity movement in Poland, uni-lateral military intervention, and the issue of compellence and deterrence during a national security crisis. Modeling and Simulation for Analyzing Global Events is an excellent book for statistics, engineering, computer science, economics, and social sciences courses on modeling and simulation at the upper-undergraduate and graduate levels. It is also an insightful reference for professionals who would like to develop modeling and simulation skills for analyzing and communicating human behavior observed in real-world events and complex global case studies.
"This book reviews methodologies in computer network simulation and modeling, illustrates the benefits of simulation in computer networks design, modeling, and analysis, and identifies the main issues that face efficient and effective computer network simulation"--Provided by publisher.