186.861 Modeling and Solving Constrained Optimization Problems
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2020S, VU, 2.0h, 3.0EC, to be held in blocked form


  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VU Lecture and Exercise

Learning outcomes

After successful completion of the course, students are able to...

- model and solve combinatorial optimization problems using Constraint Programming (CP).

- implement different methods for solving CP problems.

Subject of course

- Constraint Programming basics: fundamental concepts, types of domains (finite domains, intervals, sets), constraints, search, branch and bound
- CP modeling techniques: global constraints, redundant constraints, symmetry elimination, special-purpose constraints (e.g., scheduling), modeling of optimization problems, problem reduction
- CP languages/libraries: GECODE, COMET, ...
- Modeling examples: n-Queens, Cryptoarithmetic, Sudoku, Scheduling, Timetabling, ...
- Basic solution methods: propagation, consistency, search
- Advanced solution methods: heuristic methods, hybrid approaches, integration with heuristic/metaheuristic techniques
- Statistical analysis of optimization algorithms
- Lab practice

Teaching methods

Lectures and solving programming assignments.

Mode of examination


Additional information


20 h  lectures
  2 h  lab practice
32 h  preparation of assignments
20 h  preparation for final oral exam
  1 h  oral exam and presentation of last assignment
75 h overall 

The course is blocked. The lecture times will be announced.




Examination modalities

Discussion of solutions for programming assignments, oral examination.

Course registration

Not necessary



No lecture notes are available.