Module overview
The module is designed to introduce a range of Management Science techniques, it is the level 1 module in the prescriptive analytics stream for the Business Analytics programmes.
This module will describe many of the classical MS problems and solution techniques and illustrate their use and effectiveness. You will have the opportunity to explore the process of understanding, formulating, solving and analysing a number of practical problems using the tools and techniques introduced in the module.
Linked modules
Pre-Requisites: MANG1007 or MANG1047 or MANG1019 or ECON1005 or ECON1008
Aims and Objectives
Learning Outcomes
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- apply a number of the core MS approaches;
- evaluate the outcome of the MS approaches with respect to sensitivity and uncertainty.
- apply MS in practical contexts in a considered manner;
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- the practical use of MS approaches.
- the range of techniques, tools, models, methods and approaches;
- the nature of MS, its history and the context of its contribution to management;
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- use rational analytic skills.
- use quantitative modelling approaches;
- use problem-solving skills;
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- use specialised software to solve mathematical programming problems and perform discrete- event simulations
Syllabus
Management Science: history, context, and the management science process. Mathematical modelling: the development and formulation of a mathematical model.
Solution approaches for management problems; specifically, Linear and Integer Programming, Inventory Theory, Simulation, Queuing Theory, Network Models and Project Scheduling.
The interpretation of the mathematical models and solutions in management science.
Learning and Teaching
Teaching and learning methods
Teaching methods include:
- Lectures that will cover the taught material and include example problems and worked solutions and class discussion.
- Classes where problem example sheets will be set in advance to be discussed and solved in the class.
- Computer workshops where tutorial sheets will be provided on simulation and optimisation.
Learning activities include:
- Computer workshops on Linear Programming
- Computer workshops simulation modelling
- In class debate and discussion
- Private study
Type | Hours |
---|---|
Wider reading or practice | 5 |
Revision | 20 |
Lecture | 24 |
Tutorial | 10 |
Follow-up work | 8 |
Completion of assessment task | 15 |
Preparation for scheduled sessions | 68 |
Total study time | 150 |
Resources & Reading list
Textbooks
Anderson D.R., Sweeney D.J., Williams T.A., and Wisniewski, M (2009). An Introduction to Management Science: Quantitative Approaches to Decision Making. Cengage Learning.
Albright S. C., and Winston W. L. (2007). Management Science Modelling. Thomson South-Western.
Hillier F.S., and Lieberman G.J. (2005). Introduction to Operations Research. McGraw-Hill.
Assessment
Formative
This is how we’ll give you feedback as you are learning. It is not a formal test or exam.
Class participation
- Assessment Type: Formative
- Feedback:
- Final Assessment: No
- Group Work: No
Summative
This is how we’ll formally assess what you have learned in this module.
Method | Percentage contribution |
---|---|
Report | 20% |
Examination | 80% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
Method | Percentage contribution |
---|---|
Examination | 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 |
---|---|
Examination | 80% |
Report | 20% |
Repeat Information
Repeat type: Internal & External