Course overview
This course is focused on equipping learners with simulation techniques to underpin decision making. Simulation is widely used to model systems, to evaluate risk, and to optimise objective functions, with the goal to inform decisions. Building up from uniform random generation, some of the key simulation techniques used for efficient simulation to support decision-making will be presented.
- Introductory Concepts
- Discrete-Event Simulation in Detail
- The Final Product
Course learning outcomes
- Communicate how randomness and controlled variation can be used to model complex systems in a range of application domains such as industry, health, and transportation.
- Create a model of a real-world problem specified in words and implement it as a discrete-event simulation.
- Collect data and test, verify and validate a simulation.
- Explore scenarios using simulation to elicit and compare possibilities.
- Design simulation-based workflows to support decision-making in real-world contexts and explain the process.
Degree list
The following degrees include this course