Lecture
Approximation Algorithms
Lecturer
Description
A large fraction of interesting dicrete optimization problems are NP-hard, that means there is no hope in finding exact, optimum solutions efficiently – all known algorithms for this goal have exponential running time. Hence a growing field in theoretical computer science and discrete mathematics deals with approximation algorithms. These algorithms need only polynomial time and obtain solutions whose values are within a provably small ratio from the optimum. We will present fundamental approximation algorithms for example for
- Steiner tree
- k-Center
- TSP
- Set Cover
- Knapsack
- Multi Constraint Knapsack
- Bin Packing (including the AFPTAS by Karmarkar & Karp)
- Scheduling on unrelated parallel machines
- Scheduling on parallel identical machines
- Facility Location
- Tree embeddings
- MaxCut (via semidefinite programming)
- Max-2-Sat (via semidefinite programming)
The lectures and the exercises will be given in English. The only prerequisit is a basic knowledge of algorithms. Please note that this is a theory course, hence there will be no kind of implementation/coding. This is a 4-credit doctoral course. The ID is MATH-724.
Schedule
Lectures: Wednesday, 14:15-15:45, ELD 120 (starting from 24.02.10)
Exercises: Wednesday, 16:00-17:30, ELD 120 (starting from 03.03.10)
On May 5, lecture and exercise are moved to room AAC 132 (due to the Balelec festival).
Slides
Slides of Lecture (last update: June 2)
Exercises
Exercise sheet 10 (updated on May 11) Solution 10
Exam
There will be an oral exam at the end of the semester. This is a 4-credit course. Here is a link to the course book webpage page.