| Module Code | STU11004 |
| Module Name | Introduction to Management Science |
| ECTS Weighting[1] | 10 ECTS |
| Semester taught | Semester 1 & 2 |
| Module Coordinator/s | John McDonagh |
Module Learning Outcomes
On successful completion of this Module, students will be able to:
Semester 1
- L01: Explain why the value of money decreases as a function of how far in the future it will be available.
- L02: Compute the simple and compound interest of any amount of money, the value of an annuity and the payment of an amortised loan.
- L03: Identify and solve problems using dynamic programming.
- L04: Compute the shortest spanning tree of a network and the shortest path between two points in a network.
- L05: Derive the maximal flow through a network.
- L06: Compute the optimal inventory policy for the classic formulation, and also with constant receipt and shortages.
- L07: Explain risk averse and risk prone behaviour, give examples of each and demonstrate that decreasing marginal worth leads to risk averse behaviour.
- L08: Calculate properties of a queueing system from information about number of servers, arrival rates and service rate
Semester 2
- L09: Compute basic forecasts of a time series variable and explain how you would assess their accuracy.
- L10: Identify and solve problems using linear programming.
- L11: Understand the decision analysis tools used in Management Science, and carry out analysis using tools such as decision trees and utility.
Module Content
This module covers a range of subjects in Management Science at an introductory level. The objectives of the module are to give students an overview of the subject, to teach important basic techniques and introduce systematic thinking about problems. The first semester begins with the topic of the time value of money, and then looks at the theory of queues, classic network problems, inventory control and then finishes with dynamic programming. The second semester looks at basic forecasting, linear programming and the different decision making tools used in Management Science . The module will use real-world Management Science problems to illustrate concepts and models.
Teaching and learning Methods
There will be three hours of lectures each week.
Assessment Details
| Assessment Component | Brief Description | Learning Outcomes Addressed | % of total | Week set | Week due |
| Examination | In-person Exam (2hrs) | First Semester | 35% | n/a | n/a |
| Coursework | Assignments | First Semester | 15% | TBD | TBD |
| Examination | In-person Exam (2hrs) | Second Semester | 35% | n/a | n/a |
| Coursework | Assignments | Second Semester | 15% | TBD | TBD |
Reassessment Details
Reassessment is an in-person Exam (2hrs).
Contact Hours and Indicative Student Workload
| Contact Hours (scheduled hours per student over full module), broken down by: | 66 hours | |
| Lecture | 66 hours | |
| Laboratory | 0 hours | |
| tutorial or seminar | 0 hours | |
| Other | 0 hours | |
| Independent study (outside scheduled contact hours), broken down by: | 144 hours | |
| preparation for classes and review of material (including preparation for examination, if applicable) | 132 hours | |
| completion of assessments (including examination, if applicable) | 12 hours | |
| Total Hours | 210 hours |
Recommended Reading List
A full reading list will be provided at the start of each semester. No one textbook covers the entire module, but some parts of the following books will be useful.
An Introduction to Management Science: Quantitative Approaches to Decision Making (3rd Edition), David Anderson et al. Cengage. 2017.
Introduction to Management Science (10th Edition) by Bernard W. Taylor. Pearson. 2012.
Module Pre-requisites
Prerequisite modules: None
Other/alternative non-module prerequisites: None
Module Co-requisites
None