After successful completion of the course, students are able to

• apply the basics of scheduling theory
• classify scheduling problems
• apply and analyze approximation algorithms for scheduling problems
• apply scheduling theory in a parallel computing context

The course gives an introduction into the basics of scheduling theory, but will also highlight practical aspects when solving scheduling problems. The course introduces basic concepts and notation used in scheduling research. Then, selected topics are discussed in more detail, such as: shop scheduling, scheduling with parallel tasks, online scheduling, approximation algorithms in scheduling, divisible load scheduling, simulations and scheduling.

Lectures, active aprticipatiopn, project work

Books

• Florian Jaehn and Erwin Pesch. Ablaufplanung. Springer, 2014
• Oliver Sinnen. Task Scheduling for Parallel Systems. Wiley, 2007
• Yves Robert and Frédéric Vivien, eds. Introduction to Scheduling. Chapman & Hall/CRC, 2010
• Maciej Drozdowski. Scheduling for Parallel Processing. Springer, 2009
• Michael L. Pinedo. Scheduling - Theory, Algorithms, and Systems. 3rd ed. Springer, 2008
• Peter Brucker. Scheduling algorithms. 5th ed. Springer, 2007
• Joseph Y-T. Leung, ed. Handbook of Scheduling: Algorithms, Models and Performance Analysis. Chapman & Hall/CRC, 2004

ECTS Breakdown:

• Lectures: 1 ECTS
• Study: 1 ECTS
• Exercises: 1 ECTS

• Planning, Overview: 2h
• Lectures: 24h (ca. 12 times 2h)
• Exercises, presentation: 6h (ca. 3 times 2h)
• Own Study: 20h
• Preparation for exercises: 23h

Total: 25h = 3ECTS

Project submission, project presentation, oral examination

Introduction to Parallel Computing