MXB232 Introduction to Operations Research
To view more information for this unit, select Unit Outline from the list below. Please note the teaching period for which the Unit Outline is relevant.
| Unit code: | MXB232 |
|---|---|
| Equivalent(s): | MAB315 |
| Assumed Knowledge: | MXB100 or Senior Mathematics C or Senior Specialist Mathematics is assumed knowledge. |
| Credit points: | 12 |
| Timetable | Details in HiQ, if available |
| Availabilities |
|
| CSP student contribution | $578 |
| Domestic tuition unit fee | $3,528 |
| International unit fee | $4,632 |
Unit Outline: Semester 1 2025, Gardens Point, Internal
| Unit code: | MXB232 |
|---|---|
| Credit points: | 12 |
| Equivalent: | MAB315 |
| Coordinator: | Kate Helmstedt | kate.helmstedt@qut.edu.au |
Overview
Operations Research (OR) is a mathematical approach to decision making. The predominant goal of OR is to determine how best to design, operate, manage, and predict behaviour of complex systems. The cornerstone of OR is formulating and solving mathematical or computational models to extract the best, or optimal, decisions. The purpose of this introductory unit is to introduce students to foundational OR methods and techniques to solve management and optimisation problems. It provides the theoretical foundation for future studies in OR and builds upon earlier studies in linear algebra. This unit aims to develop students’ ability to apply various OR methods, algorithms, and techniques in the solution of practical, real-world problems in contexts such as the environment, agriculture, industry, finance, and healthcare.
Learning Outcomes
On successful completion of this unit you will be able to:
- Demonstrate knowledge of the principles, concepts and techniques in the field of Operations Research.
- Formulate a real-life problem in mathematical terms and apply operations research techniques, tools and methods to analyse and solve it.
- Use mathematical software to explore and solve introductory operations research problems
- Use critical thinking skills to select and apply appropriate operations research methods to analyse and solve problems, both familiar and unfamiliar, in a variety of fields both applied and abstract.
- Communicate the solution to a problem both quantitatively and qualitatively, for both mathematical and non-mathematical audiences.
Content
The general nature of Operations Research. Fundamentals of linear programming. Formulation of linear programming problems. Solution of linear programming problems using graphical method. The simplex method. Analysis of linear programming models and their outputs, including sensitivity analysis and dual programs. Network analysis, including critical path method. Transportation, transshipment, and assignment problems. Linear programming with multiple decision-makers. Computational approaches to solving linear programming problems, and analysis of output.
Learning Approaches
This unit is available for you to study in either on-campus or online mode. You will be provided with learning resources including pre-recorded videos, readings and formative quizzes that you can access flexibly to prepare for your timetabled learning activities. The pre-recorded videos will provide you with theoretical background and concepts applied in problem solving processes, and the formative quizzes are for you to check your understanding of the new concepts.
The timetabled sessions are an important opportunity for you to interact directly with the teaching team and ask for help or clarification when needed. The timetabled interactive lecture sessions will emphasise important concepts and work through additional example problems relevant for your assessment. In the timetabled workshops you will solve a range of example problems, from purely mathematical exercises to real-world applications.
Feedback on Learning and Assessment
Formative feedback will be provided for the in-semester assessment items by way of written comments on the assessment items, student perusal of the marked assessment piece and informal interview as required.
Summative feedback will be provided throughout the semester with progressive posting of results via Canvas.
Assessment
Overview
The assessment items in this unit are designed to determine your level of competency in meeting the unit outcomes while providing you with a range of tasks with varying levels of skill development and difficulty.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Problem Solving Task
This assessment will be completely individually. The task will assesses early weeks of the unit. This will give you an indication of your progress in this unit.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Case Study
This assessment item will require you to analyse a real-world case study and use linear programming techniques and common extensions to linear programming to formulate, solve, and analyse problems derived from real-world decisions.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Examination (invigilated)
This supervised examination will assess your knowledge and skills in using the techniques studied throughout the unit.
The examination will require attendance at a local testing centre. For students enrolled as internal or on-campus, the local testing centre will be on QUT campus. For students enrolled as online, QUT Examinations will provide local testing centre information.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Resources
There is no set text for this unit, although the following reference text may be consulted as a complement to the lecture notes (optional):
1. Hillier, F.S. and Lieberman, G.J. (2014), Introduction to Operations Research, McGraw Hill.
There are many other reference texts for this unit, many of which can be located in the library. There are also many online resources such as lecture notes and some e-books that can be found online. Other example reference texts are listed below.
2. Winston, W.L. (2004), Operations Research Applications and Algorithms, Boston: Duxbury Press
3. Taha, H.A. ( 2006), Operations Research. An Introduction, Prentice Hall.
Risk Assessment Statement
There are no out of the ordinary risks associated with this unit, as all classes will be held in ordinary lecture theatres. Emergency exits and assembly areas will be pointed out in the first few lectures. You are referred to the University policy on health and safety.
http://www.mopp.qut.edu.au/A/A_09_01.jsp
Standards/Competencies
This unit is designed to support your development of the following standards\competencies.
Engineers Australia Stage 1 Competency Standard for Professional Engineer
1: Knowledge and Skill Base
Relates to: Problem Solving Task, Case Study, Examination (invigilated)
Relates to: Problem Solving Task, Case Study, Examination (invigilated)
2: Engineering Application Ability
Relates to: Problem Solving Task, Case Study
Relates to: Problem Solving Task, Case Study, Examination (invigilated)
3: Professional and Personal Attributes
Relates to: Problem Solving Task, Case Study, Examination (invigilated)
Unit Outline: Semester 1 2025, Online
| Unit code: | MXB232 |
|---|---|
| Credit points: | 12 |
| Equivalent: | MAB315 |
Overview
Operations Research (OR) is a mathematical approach to decision making. The predominant goal of OR is to determine how best to design, operate, manage, and predict behaviour of complex systems. The cornerstone of OR is formulating and solving mathematical or computational models to extract the best, or optimal, decisions. The purpose of this introductory unit is to introduce students to foundational OR methods and techniques to solve management and optimisation problems. It provides the theoretical foundation for future studies in OR and builds upon earlier studies in linear algebra. This unit aims to develop students’ ability to apply various OR methods, algorithms, and techniques in the solution of practical, real-world problems in contexts such as the environment, agriculture, industry, finance, and healthcare.
Learning Outcomes
On successful completion of this unit you will be able to:
- Demonstrate knowledge of the principles, concepts and techniques in the field of Operations Research.
- Formulate a real-life problem in mathematical terms and apply operations research techniques, tools and methods to analyse and solve it.
- Use mathematical software to explore and solve introductory operations research problems
- Use critical thinking skills to select and apply appropriate operations research methods to analyse and solve problems, both familiar and unfamiliar, in a variety of fields both applied and abstract.
- Communicate the solution to a problem both quantitatively and qualitatively, for both mathematical and non-mathematical audiences.
Content
The general nature of Operations Research. Fundamentals of linear programming. Formulation of linear programming problems. Solution of linear programming problems using graphical method. The simplex method. Analysis of linear programming models and their outputs, including sensitivity analysis and dual programs. Network analysis, including critical path method. Transportation, transshipment, and assignment problems. Linear programming with multiple decision-makers. Computational approaches to solving linear programming problems, and analysis of output.
Learning Approaches
This unit is available for you to study in either on-campus or online mode. You will be provided with learning resources including pre-recorded videos, readings and formative quizzes that you can access flexibly to prepare for your timetabled learning activities. The pre-recorded videos will provide you with theoretical background and concepts applied in problem solving processes, and the formative quizzes are for you to check your understanding of the new concepts.
The timetabled sessions are an important opportunity for you to interact directly with the teaching team and ask for help or clarification when needed. The timetabled interactive lecture sessions will emphasise important concepts and work through additional example problems relevant for your assessment. In the timetabled workshops you will solve a range of example problems, from purely mathematical exercises to real-world applications.
Feedback on Learning and Assessment
Formative feedback will be provided for the in-semester assessment items by way of written comments on the assessment items, student perusal of the marked assessment piece and informal interview as required.
Summative feedback will be provided throughout the semester with progressive posting of results via Canvas.
Assessment
Overview
The assessment items in this unit are designed to determine your level of competency in meeting the unit outcomes while providing you with a range of tasks with varying levels of skill development and difficulty.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Problem Solving Task
This assessment will be completely individually. The task will assesses early weeks of the unit. This will give you an indication of your progress in this unit.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Case Study
This assessment item will require you to analyse a real-world case study and use linear programming techniques and common extensions to linear programming to formulate, solve, and analyse problems derived from real-world decisions.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Examination (invigilated)
This supervised examination will assess your knowledge and skills in using the techniques studied throughout the unit.
The examination will require attendance at a local testing centre. For students enrolled as internal or on-campus, the local testing centre will be on QUT campus. For students enrolled as online, QUT Examinations will provide local testing centre information.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Resources
There is no set text for this unit, although the following reference text may be consulted as a complement to the lecture notes (optional):
1. Hillier, F.S. and Lieberman, G.J. (2014), Introduction to Operations Research, McGraw Hill.
There are many other reference texts for this unit, many of which can be located in the library. There are also many online resources such as lecture notes and some e-books that can be found online. Other example reference texts are listed below.
2. Winston, W.L. (2004), Operations Research Applications and Algorithms, Boston: Duxbury Press
3. Taha, H.A. ( 2006), Operations Research. An Introduction, Prentice Hall.
Risk Assessment Statement
There are no out of the ordinary risks associated with this unit, as all classes will be held in ordinary lecture theatres. Emergency exits and assembly areas will be pointed out in the first few lectures. You are referred to the University policy on health and safety.
http://www.mopp.qut.edu.au/A/A_09_01.jsp
Standards/Competencies
This unit is designed to support your development of the following standards\competencies.
Engineers Australia Stage 1 Competency Standard for Professional Engineer
1: Knowledge and Skill Base
Relates to: Problem Solving Task, Case Study, Examination (invigilated)
Relates to: Problem Solving Task, Case Study, Examination (invigilated)
2: Engineering Application Ability
Relates to: Problem Solving Task, Case Study
Relates to: Problem Solving Task, Case Study, Examination (invigilated)
3: Professional and Personal Attributes
Relates to: Problem Solving Task, Case Study, Examination (invigilated)