Single-Course English 5 ECTS

Optimization using metaheuristics

Overall Course Objectives

To give a thorough introduction to the use of metaheuristics for optimization for solving real-world optimizaton problems, where a trade-off is necessary between solution quality and solution time.

Learning Objectives

  • Solve complex and/or large optimization problems using meta-heuristics.
  • Identify what are the most appropriate meta-heuristics for a specific optimization problem.
  • Device a problem representation that allows a specific problem to be optimized using a meta-heuristic.
  • Specialize a meta-heuristic such that it can be applied to a specific optimization problem.
  • Implement a metaheuristic such that it can be applied to a specific optimization problem.
  • Test a meta-heuristic such that its efficiency can be reliably evaluated.
  • Describe in written form the adaptation of a meta-heuristic to a specific problem formulation.
  • Understand the difference between the diversification and intensification strategies of different meta-heuristic frameworks.

Course Content

Many interesting optimization problems cannot be solved using standard solvers dues to their size and complexity.

A pragmatic approach to optimization is to use tailored computer algorithms to test a large number of solutions in order to find a good feasible solution. Such algorithms are called heuristics. Those algorithms do not guarantee to find optimal solutions but attempt to identify good solutions. There exist a number of more general algorithmic frameworks which can be applied to a wide variety of optimization problems. Those are the so-called meta-heuristics. In this course a number of these meta-heuristics will be presented:

– Simulated Annealing
– Genetic Algorithms/Evolutionary Algorithms
– TABU search

As this field is constantly developing, the content of the course is constantly updated. The exercises in the course will be in the computing language Julia, hence prior experience with Julia is an advantage.

Recommended prerequisites

42101, Introduction to Operations Research and programming experience. The course heavily relies on your ability to program.

Teaching Method

Lectures, excercises and project work.

See course in the course database.





13 weeks




DTU Lyngby Campus

Course code 42137
Course type Candidate
Semester start Week 5
Semester end Week 19
Days Mon 13-17

7.500,00 DKK