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October 2018
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Modelling and Simulation of Stochastic Systems

Go to this course in the University Course Planner.

Description

The course provides students with the skills to analyse and design systems using modelling and simulation techniques. Case studies will be undertaken involving hands-on use of simulation packages. The application of simulation in areas such as manufacturing, telecommunications and transport will be investigated. At the end of this course, students will be capable of identifying practical situations where simulation modelling can be helpful, reporting to management on how they would undertake such a project, collecting relevant data, building and validating a model, analysing the output and reporting their findings to management. Students complete a project in groups of two or three, write a concise summary of what they have done and report their findings to the class. The project report at the end of this course should be a substantial document that is a record of a student's practical ability in simulation modelling, which can also become part of a portfolio or CV.


Objective

To introduce the basic concepts involved in designing a system model and to introduce the use of a simulation package or a simulation program such as Opnet or Planimate. We also aim to improve students' presentation skills, both verbal and written and to improve students' ability to work as part of a team through an extended project. To achieve these goals, we give students the opportunity to follow a system modelling and simulation exercise from conception through to completion. At the end of this course, students will be capable of identifying practical situations where simulation modelling can be helpful, reporting to management on how they would undertake such a project, collecting relevant data, building and validating a model, analysing the output and reporting their findings to management.


Content

Topics covered are: Introduction to simulation, hand simulation, introduction to a simulation package, review of basic probabilty theory, introduction to random number generation, generation of random variates, anaylsis of simulation output, variance reduction techniques and basic analytic queeing models.

 
YearSemesterLevelUnits
2013143
David Green
Lecturer for this course

Graduate attributes


Linkage future

This subject will be very useful for students in engineering disciplines and in Computer Science who wish to improve their system modelling skills.


Recommended text

Notes will be provided. Simulation Modelling and Analysis}, Averill M. Law and W. David Kelton, 658.40352 L415s Simulation of Manufacturing Systems}, A. Carrie, 670.42011 C316s Simulation}, Sheldon Ross, 519.2 R826s