Last modified: 14 Nov 2025 14:16
Linear optimisation is a method to achieve the best outcome in a mathematical model whose requirements are represented by linear relationships. It is widely used in business and economics, and is also utilised for some engineering problems. Industries that use linear programming models include transportation, energy, telecommunications and manufacturing. It has proved useful in modeling diverse types routing, scheduling, assignment and design.
| Study Type | Undergraduate | Level | 4 |
|---|---|---|---|
| Term | First Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
|
||
In many real life problems one is required to find optimal solutions, namely a solution which, generally speaking, either minimises cost or maximises gain. To do so, one models the problem mathematically, and then applies the appropriate mathematical techniques to find the optimal solution. In this course students will learn how to formulate optimisation problems mathematically and study the relevant techniques from analysis and algebra which are useful in solving them, for example the Simplex Algorithm developed by Dantzing in 1947. Applications to “real life†problems and the use of computer software to solve them will also be discussed.
Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 30 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Apply | Formulate constrained global extrema problems in Euclidean space, and solve them using a combination of differential techniques and the method of Lagrange multipliers. |
| Procedural | Apply | Formulate unconstrained local extrema problems in Euclidean space, and solve them, in simple cases, using the study of critical points. |
| Procedural | Understand | Understand the theory behind optimisation problems in Euclidean space. |
| Assessment Type | Summative | Weighting | 40 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Analyse | Recognise linear optimisation problems, and compare their level of complexity to that of non-linear problems. |
| Procedural | Apply | Formulate mathematically, optimisation problems specified in words. |
| Procedural | Apply | Formulate constrained global extrema problems in Euclidean space, and solve them using a combination of differential techniques and the method of Lagrange multipliers. |
| Procedural | Apply | Formulate unconstrained local extrema problems in Euclidean space, and solve them, in simple cases, using the study of critical points. |
| Procedural | Apply | Formulate a given linear optimisation problem in terms of the simplex algorithm and solve it in simple cases. |
| Procedural | Understand | Understand the theory behind optimisation problems in Euclidean space. |
| Assessment Type | Summative | Weighting | 30 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Analyse | Recognise linear optimisation problems, and compare their level of complexity to that of non-linear problems. |
| Procedural | Apply | Formulate a given linear optimisation problem in terms of the simplex algorithm and solve it in simple cases. |
There are no assessments for this course.
| Assessment Type | Summative | Weighting | 100 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
|
|
||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Apply | Use computing tools to aid in solving optimisation problems of a relatively complex nature. |
| Procedural | Analyse | Recognise linear optimisation problems, and compare their level of complexity to that of non-linear problems. |
| Procedural | Apply | Formulate constrained global extrema problems in Euclidean space, and solve them using a combination of differential techniques and the method of Lagrange multipliers. |
| Procedural | Understand | Understand the theory behind optimisation problems in Euclidean space. |
| Procedural | Apply | Formulate mathematically, optimisation problems specified in words. |
| Procedural | Apply | Formulate a given linear optimisation problem in terms of the simplex algorithm and solve it in simple cases. |
| Procedural | Apply | Formulate unconstrained local extrema problems in Euclidean space, and solve them, in simple cases, using the study of critical points. |
We have detected that you are have compatibility mode enabled or are using an old version of Internet Explorer. You either need to switch off compatibility mode for this site or upgrade your browser.
