Discrete Event Simulation Jerry Banks
Selina Basua
This text provides a basic treatment of discrete-event simulation, including the proper collection and analysis of data, the use of analytic techniques, verification and validation of models, and designing simulation experiments. It offers an up-to-date treatment of simulation of manufacturing and material handling systems, computer systems, and computer networks.
Students and instructors will find a variety of resources at the associated website, www.bcnn.net, including simulation source code for download, additional exercises and solutions, web links and errata.
N2 - This text provides a basic treatment of discrete-event simulation, one of the most widely used operations research and management science tools for dealing with system design in the presence of uncertainty. Proper collection and analysis of data, use of analytic techniques, verification and validation of models and the appropriate design of simulation experiments are treated extensively. Readily understandable to those having a basic familiarity with differential and integral calculus, probability theory and elementary statistics. The Third Edition reorganizes, updates and expands coverage to reflect the most recent developments in software and methodology, and adds a chapter on the simulation of computer systems.
AB - This text provides a basic treatment of discrete-event simulation, one of the most widely used operations research and management science tools for dealing with system design in the presence of uncertainty. Proper collection and analysis of data, use of analytic techniques, verification and validation of models and the appropriate design of simulation experiments are treated extensively. Readily understandable to those having a basic familiarity with differential and integral calculus, probability theory and elementary statistics. The Third Edition reorganizes, updates and expands coverage to reflect the most recent developments in software and methodology, and adds a chapter on the simulation of computer systems.
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This course gives an introduction to modeling, analysis and simulation of computer and networking systems. The focus of the course is on discrete-event simulation. Simulation is widely used to evaluate systems in general, computer and communication networks in particular. In this course we will emphasize the simulation of wired and wireless communication systems. Some topics of the course are:
This book has stood the test of time. It was first published in 1984 and the original structure has remained broadly in place since then. The fourth edition updates sections on simulation software packages and programming trends, and there are extra statistical treatments for input modelling, validation and output analysis. A new chapter has been included on using simulation to model computer networks, complementing two others on manufacturing and computer systems.
The material is targeted towards undergraduate and postgraduate simulation courses in subjects such as operational research, computer science, engineering and business. It is divided into five parts. The first part introduces discrete-event simulation by examining its history, principles and software, and includes a chapter of motivating examples. The examples are designed to be worked through using a spreadsheet and Excel solutions may be downloaded from an associated website. The next two parts look at some of the technical aspects upon which a sound simulation project is based; mathematical and statistical models, and random numbers. The fourth part is the longest and examines the analysis of simulation data from input modelling, through verification and validation, to analysis of experimental output. The final part provides applications of simulation. The book reads well and presentation is very clear throughout. I found a nice continuity between the different parts and chapters, yet that each could be read on its own.
I think that the book makes a good introduction to discrete-event simulation. It is full of examples to motivate the usefulness of simulation and help the reader understand the technical content. More advanced simulation aspects such as optimization and meta-modelling are covered, and references provide pointers to further information. However, the authors perhaps miss a trick by not covering design of experiments for simulation models in much detail. This part of the simulation modelling process is important because confidence in findings is reliant on how the model is run.
This course introduces discrete-event simulation techniques including model design and development, comparison to analytical models, input data preparation, random number generation, output statistical analysis, and model validation. Using these techniques, students will: model real-world systems, implement the model as a computer program (we will use C/C++ with CSIM library), and evaluate the performance of real-world systems by analyzing the output of the model under various conditions.
After installing and running SSH: Click Quick Connect, enter xyz.cs.utsa.edu as the hostname, enter your cs account id (first initial followed by up to 7 letters of your last name) as username, thenclick connect. First time it may ask if you want to save keys etc., say yes then enter your password...
Your CS account name will usually be your first initial followed by up to 7 letters of your last name. However, account names sometimes vary because of name conflicts. New account names are posted in the lab. Your initial password is your 8-digit student ID without the leading @ sign.
Note: Turn off and put away all cell phones, iPods, and other electronic devices. You should only have class materials on your desk. You should only have the course web pages, and the classroom query software up on your screen. The instructor and TAs can observe and will record incidents of inattention, which will seriously impact the Homework/Attendance/Participation portion of your grade. Unauthorized electronic devices in use or on the desktop during class are subject to confiscation.
Note: (a) Students are not automatically dropped from a class if they stop attending the class. (b) University policy does not permit visitors in a class. (c) University policy does not permit faculty or office staff to report grades by telephone, fax, or email.
This syllabus is provided for informational purposes regarding the anticipated course content and schedule of this course. It is based upon the most recent information available onthe date of its issuance and is as accurate and complete as possible. The instructor reservesthe right to make any changes deemed necessary and/or appropriate. The instructor willmake his or her best efforts to communicate any changes in the syllabus in a timely manner.Students are responsible for being aware of these changes.
By the end of this course, successful students should have learnt the principles of simulation, modelling, and statistical analysis for discrete event systems as well as the techniques and tools to apply those principles on a computer, in particular using the simulation software package ARENA.
1. Understand the world, their country, their society, as well as themselves and have awareness of ethical problems, social rights, values and responsibility to the self and to others. 2
3. Think critically, follow innovations and developments in science and technology, demonstrate personal and organizational entrepreneurship and engage in life-long learning in various subjects; have the ability to continue to educate him/herself. 5
5. Take individual and team responsibility, function effectively and respectively as an individual and a member or a leader of a team; and have the skills to work effectively in multi-disciplinary teams. 4
1. Possess sufficient knowledge of mathematics, science and program-specific engineering topics; use theoretical and applied knowledge of these areas in complex engineering problems. 4
3. Develop, choose and use modern techniques and tools that are needed for analysis and solution of complex problems faced in engineering applications; possess knowledge of standards used in engineering applications; use information technologies effectively. 4
4. Have the ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling specified needs; apply modern design techniques for this purpose. 4
7. Possess knowledge of impact of engineering solutions in a global, economic, environmental, health and societal context; knowledge of contemporary issues; awareness on legal outcomes of engineering solutions; knowledge of behavior according to ethical principles, understanding of professional and ethical responsibility. 3
8. Have the ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. 4
1. Comprehend key concepts in biology and physiology, with emphasis on molecular genetics, biochemistry and molecular and cell biology as well as advanced mathematics and statistics. 1
2. Develop conceptual background for interfacing of biology with engineering for a professional awareness of contemporary biological research questions and the experimental and theoretical methods used to address them. 1
1. Applying fundamental and advanced knowledge of natural sciences as well as engineering principles to develop and design new materials and establish the relation between internal structure and physical properties using experimental, computational and theoretical tools. 1
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