MA424      Half Unit
Stochastic Modelling and Simulation

This information is for the 2025/26 session.

Course Convenor

Availability

Requisites

Additional requisites:

Students must have undergraduate knowledge of probability and statistics.

The course covers theory including the basics of probability and statistics, Markov chains, queueing theory, and inventory models (deterministic and stochastic). The course also covers simulation modelling, the playing-out of real-life scenarios in a (computer-based) modelling environment. This part of the course develops understanding of the theoretical basis which underpins the simulation methodology, and an appreciation of practical issues in managing a simulation modelling project. Simulation topics include generating discrete and continuous random variables, Monte Carlo simulation, discrete event simulation (DES, where we simulate queueing and inventory models), variance reduction techniques, and Markov Chain Monte Carlo methods. The course includes use of a simulation modelling software package.

10 hours of seminars and 20 hours of lectures in the Autumn Term.

This course is delivered through a combination of seminars and lectures totalling a minimum of 30 hours across Autumn Term.

Problem sets

Students will be expected to submit two pieces of coursework for feedback.

The reading will be a combination of lecture notes, lecture slides, and chapters from the following list of books.

Operations Research Methods

• F S Hillier & G J Lieberman, Introduction to Operations Research, 9th edition (2009) (7th edition of Hillier & Lieberman (2000) is also acceptable).
• Wayne Winston, Operational Research; Applications and Algorithms, Fourth/International Student Edition.

Simulation Modelling

• S Ross, Simulation, Academic Press (5th ed., 2012)
• Joseph K. Blitzstein, Jessica Hwang, Introduction to Probability, Chapman and Hall/CRC Press (2014)

Exam (60%), duration: 120 Minutes in the Spring exam period

Project (40%)