186.860 Metaheuristics and Hybrid Methods for Combinatorial Optimization Canceled
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2021W, VU, 2.5h, 4.0EC, to be held in blocked form

Course evaluation


  • Semester hours: 2.5
  • Credits: 4.0
  • Type: VU Lecture and Exercise
  • Format: Presence

Learning outcomes

After successful completion of the course, students are able to understand diverse heuristic and hybrid algorithms for solving hard combinatorial  optimization problems, to apply them in practice, and to adapt them to new problems.

Subject of course


Due to the pandemic situation, we decided to move this course into the summer term with the hope to be able to do it then in presence. It will take place in a blocked way from March 1 to March 11, each day (Mo-Fr) presumably from 12:00-15:00, but these times may still change. More details will be announced as soon as possible.

Combinatorial optimization problems arise in many aspects of human activities. Examples concern packing and cutting problems, timetabling problems, and vehicle routing problems. Many of these problems are computationally very difficult to be solved to optimality. Therefore, simple heuristics (such as greedy algorithms) and metaheuristics (such as tabu search, evolutionary algorithms, and simulated annealing) have achieved a lot of attention from the optimization community during the last decades. At the same time, the operations research community has invested considerable efforts into both exact techniques (such as algorithms based on branch & bound) and general purpose solvers that implement these state-of-the-art exact techniques. Example are CPLEX and Gurobi. This course will give an introduction to these topics. Attendees should bring a laptop with a recent Linux operating system (e.g. Ubuntu) and the GNU g++ compiler installed.

Teaching methods

Introduction and explanation of methods, discussion of examples, theoretical exercises, hands-on programming exercises, presentation and discussion of solutions.

Mode of examination


Additional information

ECTS Breakdown:

* 20 hours of theory classes (0.8 ECTS)
* 10 hours of reading homework (0.4 ECTS)
* 70 hours work on the practical project: 2.8 ECTS. Approximate division of these 70 hours:
  + Getting familiar with the given problem and the required tasks: 5 hours
  + Design and implementation of the heuristics and metaheuristics: 20 hours
  + Design and implementation of the hybrid metaheuristics: 10 hours
  + Experimental evaluation: 15 hours
  + Writing the report: 20 hours



Examination modalities

Programming assignments, discussion of results, and oral exam.

Course registration

Begin End Deregistration end
22.09.2021 00:00 20.01.2022 23:59



No lecture notes are available.

Previous knowledge

Solid knowledge in programming, algorithms and data structures.