Simulation Modelling - CB966

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Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2020 to 2021
(version 7)
Spring 7 15 (7.5) DR K Kotiadis checkmark-circle


The aim of the module is to give students hands-on experience in using industry-standard simulation modelling software in order to structure and solve complex and large-scale managerial decision problems.

The module will cover the following topics:

- Queuing theory: Students will be introduced to the basic underpinnings of queuing theory, including key assumptions, benefits, and limitations.

- Discrete-event simulation: Core theory of discrete-event simulation will be covered, including a review of simulation mechanics, how to incorporate randomness into a simulation, and the systematic analysis of simulation model results. This will be supplemented with practical training in how to build and run simulation models using commercial software. Example applications will be drawn from a variety of sectors, such as manufacturing/production, transportation, healthcare, and other service industries (e.g., banking, retail, customer service).


This module appears in the following module collections.

Contact hours

Total contact hours: 35
Private study hours: 115
Total study hours: 150

Method of assessment

Main assessment methods:
VLE Test 1: 20%
VLE Test 2: 20%
Individual Simulation Modelling Report (2000 words): 60%

Reassessment methods:
Reassessment Instrument: 100% coursework

Indicative reading

Pidd, M. (2004) Computer Simulation in Management Science. Chichester: John Wiley & Sons.

Robinson, S. (2014) Simulation: The Practice of Model Development and Use (2nd Edition). London: Palgrave Macmillan.

Winston, W.L. (2004) Operations Research: Applications and Algorithms (4th Edition). Belmont, CA: Duxbury Press

See the library reading list for this module (Canterbury)

Learning outcomes

The intended subject specific learning outcomes.

On successfully completing the module students will be able to:
- Recognise the types of business and organisational problems that can be appropriately formulated and analysed using stochastic simulation.
- Demonstrate an in depth understanding of the simulation modelling process. This includes conceptual modelling; model coding; experimentation and calibration of models; validation and verification and implementation.
- Build realistic simulation models using industry-standard software and acquire a systematic understanding of the flexibility that simulation based approaches provide managers in terms of dealing with risk and other real-world complexities.
- Demonstrate an understanding of alternative simulation paradigms such as Monte Carlo Simulation and the alternative modes of simulation (e.g. Expert Mode versus PartiSim).

The intended generic learning outcomes.
On successfully completing the module students will be able to:
- Demonstrate originality in model building, problem-solving, and numerical analysis skills to solve complex problems.
- Use advanced computer tools to solve practical problems of direct relevance to business planning.
- Communicate findings to both specialist and non-specialist audiences in a clear, yet rigorous manner.


  1. Credit level 7. Undergraduate or postgraduate masters level module.
  2. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  3. The named convenor is the convenor for the current academic session.
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