FI:IA101 Algorithmics for Hard Problems - Course Information
IA101 Algorithmics for Hard Problems
Faculty of InformaticsAutumn 2008
- Extent and Intensity
- 2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
- Teacher(s)
- prof. RNDr. Ivana Černá, CSc. (lecturer)
- Guaranteed by
- prof. RNDr. Mojmír Křetínský, CSc.
Department of Computer Science – Faculty of Informatics
Contact Person: prof. RNDr. Ivana Černá, CSc. - Timetable
- Mon 14:00–15:50 D2
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 19 fields of study the course is directly associated with, display
- Course objectives
- The course expands on courses Algorithm design I and Algorithm design II. It focuses on the design of algorithms for hard computing tasks. The course systematically explains, combines, and compares the main possibilities for attacking hard algorithmic problems like randomization, heuristics, approximation and local search.
- Syllabus
- Deterministic approaches: pseudo-polynomial-time algoirithms, parametrized complexity, branch-and-bound, lowering worst case complexity of exponential algorithms, local search, relaxation to linear programming.
- Approximation approaches: concept of approximation algorithms, classification of optimization problems, stability of approximation, inapproximability, algorithms design.
- Randomized approaches: classification of randomized algorithms and design paradigms, design of randomized algorithms, derandomization.
- Heuristics> simulated annealing, genetic algorithms.
- Literature
- VAZIRANI, Vijay V. Approximation algorithms. Berlin: Springer, 2001, xix, 378. ISBN 3540653678. info
- MOTWANI, Rajeev and Prabhakar RAGHAVAN. Randomized algorithms. Cambridge: Cambridge University Press, 1995, xiv, 476. ISBN 0521474655. info
- HROMKOVIČ, Juraj. Algorithmics for hard problems : introduction to combinatorial optimization, randomization, approximation, and heuristics. Berlin: Springer, 2001, xi, 492. ISBN 3540668608. info
- Assessment methods
- Written test
- Language of instruction
- Czech
- Further Comments
- Study Materials
The course is taught annually. - Teacher's information
- https://is.muni.cz/auth/elearning/warp.pl?fakulta=1433;obdobi=3523;kod=IA101;qurl=%2Fel%2F1433%2Fpodzim2006%2FIA101%2Findex.qwarp
- Enrolment Statistics (Autumn 2008, recent)
- Permalink: https://is.muni.cz/course/fi/autumn2008/IA101