| Module Code | STU22006 |
| Module Name | Management Science Methods |
| ECTS Weighting[1] | 10 ECTS |
| Semester taught | Semester 1 & 2 |
| Module Coordinator/s | Paula Roberts |
Module Learning Outcomes
On successful completion of this module, students will be able to:
LO1. Identify an infeasible problem, a problem with multiple solutions or the
presence of degeneracy
LO2. Describe how to find an initial basic feasible solution to a linear program
LO3. Formulate and solve linear programming problems using graphical analysis and the simplex method
LO4. Conduct a parametric analysis on a coefficient in the objective function
LO5. Define and formulate a balanced transportation problem
LO6. Formulate and solve integer programs with a branch and bound algorithm
LO7. Identify the concepts and terminology involved in Simulation Modeling
LO8. Describe different kinds of simulation techniques and be familiar with a
range of application examples
LO9. Apply a simulation using appropriate software
LO10. Describe the limitations of Simulation Modeling
Module Content
- Semester 1
- Characteristics of Linear Programming
- Formulation of Linear Programming problems
- Use of the Simplex Method for solving Linear Programming problems
- Sensitivity Analysis on the output from Linear Programming problems
- Formulation and solution of Transportation, Transhipment and Assignment problems
- Formulation of a 0 – 1 Linear Programming problem and solution using the Cutting Plane and Branch & Bound Methods
- Analysis of networks for the Postman Tour and Travelling Salesman Problems
- Other relevant mathematical models
- Semester 2
- Introduction to Simulation Modeling
- Probability Distributions and Random Number Generation
- Applications of Simulation Modeling
- Queueing Models
- Steady-state Models and Transients
- Software for Simulation
- Statistical Analysis of Output
Teaching and Learning Methods
2 hours lectures in both Semester 1 and 2
Software Assignments in Semester 2
1 hour lab per week for Semester 2
Assessment Details
| Assessment Component | Brief Description | Learning Outcomes Addressed | % of total | Week set | Week Due |
| Examination | In-Person Exam | All | 70 | n/a | n/a |
| Assignment | Linear Programming Assignment | LO1,2,3,4,5 | 15 | 3 | 10 |
| Assignment | Statistical Software Assignment | LO8,9,10 | 15 | 14 | 22 |
Reassessment Details
In-Person Exam (100%)
Contact Hours and Indicative Student Workload
| Contact Hours (scheduled hours per student over full module), broken down by: | 60 hours |
| Lecture | 44 hours |
| Laboratory | 11 hours |
| Tutorial or seminar | 5 hours |
| Other | 0 hours |
| Independent study (outside scheduled contact hours), broken down by: | 72 hours |
| Preparation for classes and review of material (including preparation for examination, if applicable | 36 hours |
| completion of assessments (including examination, if applicable) | 36 hours |
| Total Hours | 132 hours |
Recommended Reading List
Practical Management Science (6th Edition) by Wayne L. Winston, S. Christian Albright. Cengage (2019)
Introduction to Management Science (13th Edition) by Bernard W. Taylor. Pearson (2019)
An Introduction to Management Science: Quantitative Approaches to Decision Making (3rd Edition) by David Anderson, Dennis Sweeney, Thomas Williams, Mik Wisniewski, Xavier Pierron. Cengage (2017)
Module Pre-requisites
Prerequisite modules:
Other/alternative non-module prerequisites:
Module Co-requisites
None