Discrete optimization

Education facts

Code: DIT206

The course gives an introduction to modelling various optimization problems using linear programming (LP) and integer linear programming (ILP). The Simplex algorithm to solve LPs is described and analysed. The LP relaxations of ILPs are studied and analysed to design approximation algorithms. The duality theory of linear programs is studied and used to design approximation algorithms. Vector programs to model discrete optimization problems are described and relaxed to semi-definite programs (SDPs)

Entry requirements

- 7,5 credits programming in high level language like Java, Python etc - 7,5 credits basic course in calculus/analysis - 7,5 credits basic course in linear algebra Applicants must prove knowledge of English: English 6/English level 2 or the equivalent level of an internationally recognized test, for example TOEFL, IELTS.

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

• Discrete optimization

  University of Gothenburg

  GÖTEBORG

  Start date: 18 January 2027

  End date: 21 March 2027

  Pace of study: 50 %