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Lecturer(s)
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Vejmělková Ivana, Prof. Dr. Ing.
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Course content
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1. Introduction into algorithms - correctness and efficacy of algorithms, robustness, analyses, problem solving 2.-6. Algorithmical strategies - brute force, greedy, incremental algorithms, divide & conquer, dynamic programmimg, backtracking 7. Randomized algorithms 8. Data stream algorithms 9. In-place and in situ algorithms 10. Heuristics and approximate solutions 11. Algorithmical complexity in real life 12. News and trends 13. Selected interesting "recreational" problems
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Learning activities and teaching methods
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Interactive lecture, Project-based instruction, Multimedia supported teaching, Students' portfolio, Task-based study method, Individual study, Students' self-study, Self-study of literature, Practicum
- Contact hours
- 52 hours per semester
- Individual project (40)
- 40 hours per semester
- Presentation preparation (report) (1-10)
- 5 hours per semester
- Preparation for an examination (30-60)
- 40 hours per semester
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| prerequisite |
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| Knowledge |
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| Basis of algorithmics and programming, in the best case under MS Windows. |
| learning outcomes |
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| Thorough knowledge of basical algorithmic strategies and proficiency in their use to solve a particular problem with a particular type of data, knowledge of further modern methods, such as randomized, data stream and in-place algorithms, brief information about news and trends in the area of algorithmics, design of algorithms to solve particular problems. |
| teaching methods |
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| Interactive lecture |
| Practicum |
| Multimedia supported teaching |
| Task-based study method |
| Project-based instruction |
| Self-study of literature |
| Individual study |
| Students' portfolio |
| assessment methods |
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| Combined exam |
| Skills demonstration during practicum |
| Portfolio |
| Project |
| Individual presentation at a seminar |
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Recommended literature
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Dvořák, Stanislav. Dekompozice a rekursivní algoritmy. Praha : Grada, 1992. ISBN 80-85424-76-2.
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Gonnet, Gaston H.; Baeza-Yates, R. Handbook of algorithms and data structures : in Pascal and C. Wokingham : Addison-Wesley, ----. ISBN 0-201-41607-7.
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Hromkovič, Juraj. Algorithmics for hard problems : introduction to combinatorial optimization, randomization, approximation, and heuristics. 2nd ed. Berlin : Springer, 2003. ISBN 3-540-44134-4.
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Michalewicz, Z.; Fogel, D.B. How to solve it: Modern Heuristics. Springer-Verlag, 2000.
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Moret, Bernard M. E.; Shapiro, H. D. Algorithms from P to NP. Vol. 1, Design & efficiency. Redwood City : Benjamin/Cummings Publishing, 1991. ISBN 0-8053-8008-6.
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Rawlins, Gregory J. E. Compared to what? : an introduction to the analysis of algorithms. New York : Computer Science Press, 1992. ISBN 0-7167-8243-X.
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Skiena, Steven S. The algorithm design manual. New York : Springer, 1998. ISBN 0-387-94860-0.
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