• Knowledge of important planning algorithms
• Knowledge of important scheduling algorithms
• Ability to model problems occurring in practice
• Ability to solve problems occurring in practice
• Ability to find and present literature on planning and scheduling problems

Assessment
There will be an oral exam, which counts for 50%; on this you must at least 5.0 to pass.
Furthermore, there are take-home exercises, which count for 25%. Finally, each student has to present a paper, which counts for 25% as well.

The repair test requires at least a 4 for the original test.

In this course we consider problems like `at what time should we carry out a certain action' or `who is supposed to do this task at the given time'?
The first question is a typical example of a scheduling problem, whereas the second is the main question in rostering. In this course we present techniques from combinatorial optimization that can be used to solve problems like this; if no good techniques are available, then we resort to local search.
The course consists of two major subjects: Timetabling and Scheduling (which are treated in this order).
In the first part, we discuss problems that occur in practice, like determining the optimal time-table for the Dutch Railways, the planning of buses and drivers in Rotterdam, and the construction of a timetable for school. We start with `how to model a problem', which here refers to finding out what the right objective, constraints, and assumptions should be.
In the second part we give an introduction into scheduling. We expect a basic knowledge of algorithms and optimization, but small deficiencies are removed on the spot. If you have any topics that you want to be discussed in this course, then make a request.

Course form
Lectures.

Literature
Handouts.