#
FI:IA101 Algorithmics for Hard Problems - Course Information

## IA101 Algorithmics for Hard Problems

**Faculty of Informatics**

Autumn 2014

**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)
**Supervisor**- prof. RNDr. Mojmír Křetínský, CSc.

Department of Computer Science - Faculty of Informatics

Contact Person: prof. RNDr. Ivana Černá, CSc.

Supplier department: Department of Computer Science - Faculty of Informatics **Timetable**- Mon 12:00–13:50 D2
**Prerequisites**- Experience with basic techniques for design and analysis of algorithms (recursion, dynamic programming, greedy approach) as well as with basic data structures and algorithms are required.
**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 the course is directly associated with**- there are 23 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 algorithms, parametrized complexity, branch-and-bound, lowering worst case complexity of exponential algorithms.
- Approximation approaches: concept of approximation algorithms, classification of optimization problems, stability of approximation, inapproximability, algorithms design. Linear programming as a method for construction of approximative algorithms.
- Randomized approaches: classification of randomized algorithms and design paradigms, design of randomized algorithms, derandomization, randomization and approximation.
- Heuristics: local search, simulated annealing, genetic algorithms.

**Literature**- D. Williansom, D. Shmoys. The Design of Approximation Algorithms. Cambridge, 2011
- 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 - CORMEN, Thomas H., Charles E. LEISERSON and Ronald L. RIVEST.
*Introduction to algorithms*. Cambridge: MIT Press, 1989. xvii, 1028. ISBN 0070131430. info - COOK, William.
*In pursuit of the traveling salesman : mathematics at the limits of computation*. Princeton: Princeton University Press, 2012. xiii, 228. ISBN 9780691152707. info - CHVÁTAL, Václav.
*Linear programming*. New York: W.H. Freeman, 1983. xiii, 478. ISBN 0716715872. info

*recommended literature***Teaching methods**- lectures, individual homeworks and projects aiming at practical skills with designe techniques
**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/el/1433/podzim2014/IA101/index.qwarp

- Enrolment Statistics (Autumn 2014, recent)
- Permalink: https://is.muni.cz/course/fi/autumn2014/IA101