Module overview
Stochastic OR Methods provides the students with a grounding in the stochastic elements of operational research. Models and examples are given to demonstrate applications of the topics. Discrete event simulation is taught via lectures and computer workshops while Decision Theory and the basics of Queueing Theory are taught in lectures.
Aims and Objectives
Learning Outcomes
Learning Outcomes
Having successfully completed this module you will be able to:
- demonstrate skills in using computer software and programming.
- demonstrate skills in technical report writing.
- implement and analyse a discrete event simulation model using Simul8 software.
- demonstrate skills in team working.
- demonstrate knowledge and understanding of the concepts and applications of simulation, decision theory and the basics of queueing theory.
Syllabus
Simulation: The emphasis is on simulation computing skills, which are developed in computer labs based on the SIMUL8 package.
Lectures on simulation cover: the concept of randomness; and sampling from probability distributions including discrete and continuous models.
Decision Theory: Bayes’ rule, value of information, Decision trees, and the concept of utility,
Queueing Theory: Basic elements of a queue, definition of a Markov Process and applications of queuing systems.
Learning and Teaching
Teaching and learning methods
Six 2-hour OR techniques lectures
Five 1-hour OR techniques tutorial sessions
Two 2-hour simulation lectures
Three 1-hour simulation computer sessions
| Type | Hours |
|---|---|
| Wider reading or practice | 6 |
| Preparation for scheduled sessions | 12 |
| Follow-up work | 15 |
| Revision | 9 |
| Lecture | 16 |
| Practical classes and workshops | 8 |
| Completion of assessment task | 9 |
| Total study time | 75 |
Resources & Reading list
Textbooks
Nelson, BL. Stochastic Modeling: Analysis & Simulation. Dover.
Hillier, F. Introduction to Operations Research. McGraw-Hill.
Winston, WL. Operations Research: Applications and Algorithms. Duxbury.
Ross, SM. Applied Probability Models with Optimization Applications. Dover.
Assessment
Assessment strategy
Summative assesments
Coursework - on Simulation (one individual assignment & one group assignment)
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Written assessment | 70% |
| Coursework | 30% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Exam | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Exam | 100% |
Repeat Information
Repeat type: Internal & External