Module overview
The module introduces the operational research approach for modelling and solving engineering and management problems.
Linked modules
Prerequisites: MATH1054 OR MATH1055
Aims and Objectives
Learning Outcomes
Learning Outcomes
Having successfully completed this module you will be able to:
- Demonstrate knowledge and understanding of operational research techniques for simulation, production scheduling, project management, queueing analysis, simulation, inventory control and decision analysis
- Utilise suitable mathematical methods to solve these models
- Develop and run computer simulation models
- Analyse and solve some managerial problems in engineering with some of the common operational research methods and techniques
- Demonstrate writing skills
- Structure practical problems
- Build models for simple problems in managerial decision making
Syllabus
1. Discrete Event Simulation: design of a simulation model and programme, input modelling including random number generation and random variable generation, output analysis, design of simulation experiments, simulation modelling using the Simul8 software.
2. Production Scheduling: Types of scheduling models, various algorithms for single machine scheduling, list scheduling for parallel machine scheduling, Johnson’s algorithm for flow shop
scheduling, use of heuristic methods.
3. Project Management: Network representation of engineering projects, Critical Path Method for scheduling a project, project scheduling with limited resources, crashing project completion
time.
4. Queuing Theory: dynamics of a queueing system, modelling of some typical basic queues, evaluating average queue length and waiting time.
5. Decision Analysis: pay-off table for one-off decisions and discussion of decision criteria, use of decision trees for more complex environments, decision making based on sampling (with
Bayes Theorem used to calculate posterior probabilities).
6. Inventory Models: the Economic Order Quantity model, including sensitivity analysis, economic production lot size model, quantity discount models, Wagner-Whitin model for
dynamic demand
Learning and Teaching
Teaching and learning methods
The module will be taught using a combination of lectures and computer workshops.
Type | Hours |
---|---|
Independent Study | 102 |
Teaching | 48 |
Total study time | 150 |
Resources & Reading list
Textbooks
M Pidd (2004). Computer Simulation in Management Science.. Wiley.
D.R. Anderson, D.J Sweeney, , T.A. Williams (2008). An Introduction to Management Science: Quantitative Approaches to Decision Making. South-Western College Publishing.
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
Method | Percentage contribution |
---|---|
Exam | 80% |
Coursework assignment(s) | 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 Information
Repeat type: Internal & External