Job details
Flanders Make

Characterization of the performance of (offline) scheduling approaches on flexible assembly systems

Flanders Make

Flanders Make is the strategic research centre for the manufacturing industry. Our mission is to strengthen the long-term international competitiveness of the Flemish manufacturing industry. That’s why we work together with SMEs and large companies on pre-competitive, industry-driven technological research, resulting in concrete product and production innovation in the vehicle industry, the manufacturing industry, and production environments.

Goal of the internship

Different scheduling algorithms are available in literature and under development at Flanders Make. Choosing the right algorithm for a given problem is challenging since optimization performance depends on different problem properties (number of variables, constraints, type of constraints, number of dependencies, ...). One important aspect that we want to study is the impact of many dependencies between tasks on the schedule. Blocking job shop problem is the term used in academic literature to refer to scheduling problems in which many of these dependencies are present[1]. The longer the ‘dependency chains’ become, the harder it is to manually come to a feasible solution or manually improve a given solution. Quantifying the impact of ‘task dependency’, identifying other important problem properties and discovering the boundaries of different algorithms, will help in (i) selecting the best algorithm for an industrial case and (ii) combining algorithms to further improve performance.

The goal of this thesis is to experiment with state of the art and Flanders Make scheduling algorithms and cases in order to (1) select the best algorithm for a case, based on case characteristics, (2) use this selection to further improve a scheduling algorithm (3) validate the results on benchmark cases from literature.

Learning target: you will learn about

  • different scheduling algorithms, set up test cases,
  • identify relevant case characteristics that affect performance,
  • interpret and link outcomes and characteristics
  • developing scheduling algorithms for target cases.

Profile Student

  • Master student in engineering or mathematics;
  • Knowledge about discrete optimization and experience with Python is highly recommended;
  • Passionate by research and new technologies with focus on applications for machines and production environments;
  • Result oriented, responsible and proactive;
  • A good communicator, able to communicate in English;
  • Eager to learn and a team player.

Only EEA or Swiss nationals can be accepted for internships due to work permit regulations.

Practical Data


  • This assignment is proposed for a master thesis topic
  • Thesis: This assignment can only be executed by a thesis student from a Belgian university


  • The assignment is also possible for an internship of min. 3 months to max. 6 months and takes place at the offices of Flanders Make located in Lommel or Leuven, Belgium.
  • All software and hardware needed for the execution of the project will be provided by Flanders Make.

  • Location: Gaston Geenslaan 8, 3001 Leuven / Oude Diestersebaan 133, 3920 Lommel / Graaf Karel de Goedelaan 5, 8500 Kortrijk


For more information:
at the number: 011790590
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