Combinatorial Optimisation and Constraint Programming
Course, Master's level, 1DL442
Autumn 2023 Autumn 2023, Uppsala, 33%, On-campus, English
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 28 August 2023–14 January 2024
- Language of instruction
- English
- Entry requirements
-
120 credits including Basic Course in Mathematics, Algebra I, and 10 credits in computer programming or another combination of courses containing basic concepts in algebra, combinatorics, logic, graph theory, set theory and implementation of (basic) search algorithms. Proficiency in English equivalent to the Swedish upper secondary course English 6.
- Selection
-
Higher education credits in science and engineering (maximum 240 credits)
- Fees
-
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees.
- Application fee: SEK 900
- First tuition fee instalment: SEK 24,167
- Total tuition fee: SEK 24,167
- Application deadline
- 17 April 2023
- Application code
- UU-11009
Admitted or on the waiting list?
- Registration period
- 28 July 2023–4 September 2023
- Information on registration.
Autumn 2023 Autumn 2023, Uppsala, 33%, On-campus, English For exchange students
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 28 August 2023–14 January 2024
- Language of instruction
- English
- Entry requirements
-
120 credits including Basic Course in Mathematics, Algebra I, and 10 credits in computer programming or another combination of courses containing basic concepts in algebra, combinatorics, logic, graph theory, set theory and implementation of (basic) search algorithms. Proficiency in English equivalent to the Swedish upper secondary course English 6.
Admitted or on the waiting list?
- Registration period
- 28 July 2023–4 September 2023
- Information on registration.
About the course
- The use of tools for solving a combinatorial problem, by first modelling it in a solving-technology-independent constraint-based modelling language and then running the model on an off-the-shelf solver.
- Constraint consistency; constraint propagator; propagation fixpoint algorithm.
- Solving by systematic search: construction and exploration of a search tree; branching strategies; handling of an objective function for optimisation.
- Solving by (constraint-based) stochastic local search: construction and exploration of a search space; constraint violation; variable violation; move probing; search heuristics; search meta-heuristics.