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The University of Southampton

MATH6164 Stochastic OR Methods for Data Scientists

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

Module Aims

The aims of the module are to provide the students with a grounding in the stochastic elements of operations research.

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

  • demonstrate knowledge and understanding of the concepts and applications of simulation, decision theory and the basics of queueing theory.
  • demonstrate skills in technical report writing.
  • demonstrate skills in team working.
  • implement and analyse a discrete event simulation model using Simul8 software.
  • demonstrate skills in using computer software and programming.


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

Preparation for scheduled sessions12
Completion of assessment task9
Wider reading or practice6
Practical classes and workshops8
Follow-up work15
Total study time75

Resources & Reading list

Hillier, F. Introduction to Operations Research. 

Winston, WL. Operations Research: Applications and Algorithms. 

Nelson, BL. Stochastic Modeling: Analysis & Simulation. 

Ross, SM. Applied Probability Models with Optimization Applications. 


Assessment Strategy

Summative assesments Coursework - on Simulation (one individual assignment & one group assignment)


MethodPercentage contribution
Closed book Examination 70%
Coursework 30%


MethodPercentage contribution
Closed book Examination  (2 hours) 70%
Coursework 30%

Repeat Information

Repeat type: Internal & External


Costs associated with this module

Students are responsible for meeting the cost of essential textbooks, and of producing such essays, assignments, laboratory reports and dissertations as are required to fulfil the academic requirements for each programme of study.

In addition to this, students registered for this module typically also have to pay for:

Books and Stationery equipment

Course texts are provided by the library and there are no additional compulsory costs associated with the module.

Please also ensure you read the section on additional costs in the University’s Fees, Charges and Expenses Regulations in the University Calendar available at

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