A practical introduction to simulation theory and the GPSS/PC simulation language, this package is designed to help readers start modelling real-world manufacturing and service industry problems quickly. It aims to serve both as a tutorial and reference resource.
Employs the same painstaking thoroughness and accuracy in introducing the GPSS language that made the 1974 book so popular. Includes an educational version, GPSS/H from Wolverine Software, for personal computers that is as powerful, except in file size, as the package that costs commercial users over –5,000. Available in two versions: one with 5 1/4' disks, and one with 3 1/2' disks.
This book's objective is to help the reader to acquire mastery of GPSS (General Purpose Simulation System). GPSS is a simulation programming language used to build computer models for discrete event simulations. (Author).
Modern Statistical, Systems, and GPSS Simulation, Second Edition introduces the theory and implementation of discrete-event simulation. This text: establishes a theoretical basis for simulation methodology provides details of an important simulation language (GPSS - General Purpose Simulation System) integrates these two elements in a systems simulation case study Valuable additions to the second edition include coverage of random number generators with astronomic period, new entropy-based tests of uniformity, gamma variate generation, results on the GLD, and variance reduction techniques. GPSS/PC is an interactive implementation of GPSS for the IBM-PC compatible family of microcomputers. The disk accompanying Modern Statistical, Systems, and GPSS Simulation contains the limited educational version of GPSS/PC with many illustrative examples discussed in the text.
"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
This book gives detailed coverage of all the various aspects of modelling and simulation including the concept of systems. The emphasis is on digital computer simulation of discrete systems, although both analogue and digital simulation of continuous and discrete systems are discussed.
CD-ROM with a simulation system and numerous solved models is attached to the book. Distributed systems are a continuously expanding area of computer science and computer engineering. This book addresses the need for literature on modeling and simulation techniques for distributed systems. For simulation modeling of distributed systems in the book, a specific class of extended Petri nets is used that allows to easily represent the fundamental processes of any distributed system. The book is intended, first of all, as a text for related graduate-level university courses on distributed systems in computer science and computer engineering. Other computer science and computer engineering courses would also find the book useful as a source of practical information for a broad community of those graduate students who are busy with simulation in their study and research. The book can be useful also to academics who give related graduate courses or deliver research-oriented modules for graduate students. Further, the book can be helpful to system architects and developers who apply modeling and simulation techniques as a step in the design and implementation of their systems. Containing a large number of models, with commented source texts and simulation results on the attached CD-ROM, it can also serve as valuable reference book for researchers who want to develop their own models in terms of Petri nets.
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
This book provides a balanced and integrated presentation of modelling and simulation activity for both Discrete Event Dynamic Systems (DEDS) and Continuous Time Dynamic Systems (CYDS). The authors establish a clear distinction between the activity of modelling and that of simulation, maintaining this distinction throughout. The text offers a novel project-oriented approach for developing the modelling and simulation methodology, providing a solid basis for demonstrating the dependency of model structure and granularity on project goals. Comprehensive presentation of the verification and validation activities within the modelling and simulation context is also shown.
In the area of (OR/MS), particularly in simulation modeling, working contrived textbook problems does not prepare one well for modeling the kinds of problems one finds in the real world. This book presents three kinds of real world simulation problems from the author's broad experience: (1) problems that the author has solved as an industrial consultant or advisor, (2) problems he has had his students study for local businesses, and (3) non-queuing examples. These problems represent a very broad spectrum of the kinds of problems that simulation modeling can address. Since most simulation modeling software is somewhat problem-independent, the conceptual and modeling experience gained by simulating the problems in this book using any simulation software should prepare one well for simulating problems in other areas not found here. A helpful Instructors Manual is available for faculty.