This course offers an introduction to the topics of combinatorial optimization with focus on scheduling.

Scheduling deals with problems such as:

· In which order should certain tasks be accomplished?

· How should available resources be allocated to tasks?

We can encounter these types of problems, for example, when

· Creating timetables for schools and universities: How should be choose timeslots and rooms for courses so that the students have no time conflicts?

· Planning surgeries or other medical treatments in hospital: In which operating theater and at what time should surgeries be planned so that the capacities are ideally used?

· Planning advertising campaign: In which types of media (and which timeslots) should we place our advertisement so that we reach as many possible customers as possible?

· Managing a sport event: How should we plan games in a tournament so that we avoid time conflict and also take sponsor’s interests into account?

· Planning production: How should we plan production steps and allocate machines so that we minimize production delays?

As the above examples suggest, scheduling tasks includes certain optimality criteria. In this course we will study methods of combinatorial optimization that can help us solve these kinds of problems. We will cover topics such as:

· Graph theory

· Dynamic programming

· Integer linear programming and approximations

      - Heuristics and metaheuristics

This course should provide students with basic knowledge in areas of sequencing and scheduling, combinatorial optimization and graph theory. At the end of the course, students should be able to understand and use basic methods.

Attendance is compulsory; students can miss 20% of the course units.

The course will consist of lectures where the methods will be discussed.

Students are provided with DataCamp classroom access for a semester for their own use. Access information is sent via email to course members.

The assessment will consist of

• homework (20% weight)
• project (40% weight)
• written exam (40% weight)

Students need at least 50% to successfully pass the course.

STEOP Mathematics course.

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