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Last modified: 25 Mar 2016 11:35

Course Overview

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. Applications to “real life” problems and the use of computer software to solve them will also be discussed.

Course Details

Study Type Undergraduate Level 3
Session First Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus None. Sustained Study No
  • Professor Vassili Gorbunov

Qualification Prerequisites


What courses & programmes must have been taken before this course?

What other courses must be taken with this course?


What courses cannot be taken with this course?


Are there a limited number of places available?


Course Description

  • Introduction to the analysis in several variables.
  • Convex sets, convex functions.
  • Linear optimisation.
  • Simplex method.
  • Two phase simplex method.
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Degree Programmes for which this Course is Prescribed

  • Mathematics Major

Contact Teaching Time

56 hours

This is the total time spent in lectures, tutorials and other class teaching.

Teaching Breakdown


1st Attempt: 1 two-hour written examination (80%); in-course assessment (20%). Resit: 1 two-hour examination (maximum of 100% resit and 80% resit with 20% in-course assessment). Only the marks obtained on first sitting can be used for Honours classification.

Formative Assessment

Informal assessment of weekly homework through discussions in tutorials.


In-course assignments will normally be marked within one week and feedback provided to students in tutorials. Students will be invited to contact Course Coordinators for feedback on the final examination.

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