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Discrete event simulation lets us build computer models of facilities and systems. Forecasting methods help us to predict demand for goods and services. This course develops the understanding and skills to apply these two techniques to practical problems in business, using modern software. We also cover the data analysis skills to model the inputs for these and other OR/OM techniques.
By the end of this course you should be able to:Collect and measure data so as to fit probability distributions so as to model elements of uncertainty in MS/OR models.Identify the components of a discrete-event simulation: events, activities, temporary and permanent entities. Know how at least one style of discrete-event simulation programming works, and describe the advantages and drawbacks of this style.Describe how at least one pseudo-random number generator works, how a range of random variates are produced, and identify the advantages and disadvantages of pseudo-random number generators in simulation problems.Identify and give examples of the steps in the Simulation Modelling Process. Apply appropriate steps to a particular simulation problem.Build a simple simulation model for a particular situation using Simul8, run the simulation, and produce valid results that are of value to a decision maker.Explain why extrapolative models are often used in place of causal models for short-term business forecasting.Identify and describe the components of a time series, and identify appropriate methods for forecasting a particular series.Describe the methods behind the range of models in a modern forecasting program (Forecast Pro), use the program competently, and critically evaluate the output of the program so as to produce appropriate results for decision making.Identify the steps required to set up a business forecasting system.
MSCI110 or 15 points STAT. RP: MSCI101
MSCI204
MSCI101
Don McNickle
The total workload for this course is expected to be 150 hours. You should expect to spend:Lectures 24 hoursTutorials 12 hoursAssignments 48 hoursExam Preparation 30 hoursTutorial preparation 12 hoursLecture Preparation 24 hoursTotal 150 hoursThe marks for the assessment items will be standardised before a final grade is determined. You should not regard 50% as a pass mark.
There will be extensive readings. A recommended text (possibly Winston Operations Research) will be listed after consultation with the coordinators of related courses.1. Random variables, means, variances, distributions Measuring and analysing data2. Simulation Random numbers and random variates Discrete event simulation components and styles The Simul8 package The Simulation Modelling Process Analysis of Simulation Output3. Forecasting Causal and extrapolative forecasting methods Components of a time series Smoothing and ARIMA models A business forecasting system
Departmental Academic Policies The Department assumes that you have read this document.You should also read the General Course and Examination Regulations Dishonest PracticeThe University of Canterbury considers cheating and plagiarism to be serious acts of dishonesty. All assessed work must be your own individual work unless specifically stated otherwise in the assessment guidelines. Material quoted from any other source must be clearly acknowledged. You must not copy the work of another person (student or published work) in any assessment including examinations, tests and assignments. Any person, who is found to have copied someone else's work, or to have allowed their work to be copied, will receive a fail grade for that piece of assessment and may face disciplinary action which may lead to a fine, community service or exclusion from the university.IMPORTANT: Where there are concerns regarding the authorship of written course work, a student can be required to provide a formal, oral explanation of the content of their work.Coversheets - Group and Individual
Domestic fee $655.00
International fee $2,888.00
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
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