Module overview
This module provides a practical introduction to the theories and techniques of simulation. The approach taken is very broad and covers different forms of simulation, including discrete event simulation, system dynamics and agent-based modelling. The module focuses on practical applications of simulations in a variety of contexts, and students will gain expertise in simulation software.
Aims and Objectives
Learning Outcomes
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- frame a problem and conceptualise it in a way that it can be approached using modelling.
- apply quantitative and qualitative modelling approaches;
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- the basic statistical techniques (e.g. sampling from distributions, replications, and variance reduction) underlying the methodology of simulation;
- the principles and uses of agent-based simulations;
- the principles and uses of discrete event simulation;
- how to experiment with simulation models to meet management objectives.
- the principles and uses of system dynamics;
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- apply problem-solving;
- demonstrate your numeracy to future employers;
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- create and run simulations models using modelling software.
Syllabus
- Discrete event simulation and use of modelling software
- System Dynamics and use of software
- Agent-based simulation
- Statistical aspects of simulation:
- Random numbers, sampling from distributions, confidence intervals and number of repetitions
- Validation, verification and experimentation
- Choosing distributions
- Queuing systems, events, activities and queues, activity diagrams
- Simulation software and the needs of users: graphics and interactivity
- The future of simulation: new research directions
Learning and Teaching
Teaching and learning methods
Teaching methods include:
Lectures, computer workshops, private study
Learning activities include:
Practical class exercises and games, problem solving, hands-on computer modelling
Type | Hours |
---|---|
Independent Study | 126 |
Teaching | 24 |
Total study time | 150 |
Resources & Reading list
Textbooks
John Sterman (2000). Business Dynamics, System Thinking and Modelling for a Complex World.
Michael Pidd (2006). Computer Simulation in Management Science. Wiley.
Marrtin Kunc (ed.) (2017). System Dynamics: Soft and Hard Operational Research. Springer.
Stewart Robinson (2004). The Practice of Model Development and Use. Wiley.
Akira Namatame and Shu-Heng Chen (2016). Agent-Based Modelling and Network Dynamics. Oxford University Press.
Assessment
Formative
This is how we’ll give you feedback as you are learning. It is not a formal test or exam.
Feedback
- Assessment Type: Formative
- Feedback: Individual help is given verbally during the workshops and classes; one-on-one meetings with individual students outside the module; since the coursework is in two separate parts, feedback on Part A is provided on Blackboard together with detailed written individual feedback in time for each student to enable them to improve before they submit Part B.
- Final Assessment: No
- Group Work: No
Summative
This is how we’ll formally assess what you have learned in this module.
Method | Percentage contribution |
---|---|
Exam | 80% |
Group project | 20% |
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