272-0302-00L  Approximation and Online Algorithms

SemesterSpring Semester 2015
LecturersH.‑J. Böckenhauer, D. Komm
Periodicityyearly recurring course
Language of instructionGerman



Courses

NumberTitleHoursLecturers
272-0302-00 VApproximations- und Online-Algorithmen2 hrs
Wed13:15-15:00CAB G 59 »
H.‑J. Böckenhauer, D. Komm
272-0302-00 UApproximations- und Online-Algorithmen1 hrs
Wed15:15-16:00CHN D 44 »
H.‑J. Böckenhauer, D. Komm

Catalogue data

AbstractThis lecture deals with approximative algorithms for hard optimization problems and algorithmic approaches for solving online problems as well as the limits of these approaches.
ObjectiveGet a systematic overview of different methods for designing approximative algorithms for hard optimization problems and online problems. Get to know methods for showing the limitations of these approaches.
ContentApproximation algorithms are one of the most succesful techniques to attack hard optimization problems. Here, we study the so-called approximation ratio, i.e., the ratio of the cost of the computed approximating solution and an optimal one (which is not computable efficiently).
For an online problem, the whole instance is not known in advance, but it arrives pieceweise and for every such piece a corresponding part of the definite output must be given. The quality of an algorithm for such an online problem is measured by the competitive ratio, i.e., the ratio of the cost of the computed solution and the cost of an optimal solution that could be given if the whole input was known in advance.

The contents of this lecture are
- the classification of optimization problems by the reachable approximation ratio,
- systematic methods to design approximation algorithms (e.g., greedy strategies, dynamic programming, linear programming relaxation),
- methods to show non-approximability,
- classic online problem like paging or scheduling problems and corresponding algorithms,
- randomized online algorithms,
- the design and analysis principles for online algorithms, and
- limits of the competitive ratio and the advice complexity as a way to do a deeper analysis of the complexity of online problems.
LiteratureDie Vorlesung orientiert sich teilweise an folgenden Büchern:

J. Hromkovic: Algorithmics for Hard Problems, Springer, 2004

A. Borodin, R. El-Yaniv: Online Computation and Competitive Analysis, Cambridge University Press, 1998

D. Komm: Advice and Randomization in Online Computation, 2012

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits4 credits
ExaminersD. Komm, H.-J. Böckenhauer
Typesession examination
Language of examinationGerman
RepetitionThe performance assessment is only offered in the session after the course unit. Repetition only possible after re-enrolling.
Mode of examinationwritten 120 minutes
Additional information on mode of examination20% der Note aus schriftlichen Übungen während des Semesters
Written aidsKeine
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

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ProgrammeSectionType
Certificate of Advanced Studies in Computer ScienceFocus Courses and ElectivesWInformation
Computer Science TCSpecialized Courses in Respective Subject with Educational FocusWInformation
Computer Science Teaching DiplomaSpec. Courses in Resp. Subj. w/ Educ. Focus & Further Subj. DidacticsWInformation
Computer Science MasterComputer Science Elective CoursesWInformation
Mathematics Teaching DiplomaCompulsory Elective CoursesWInformation
Computational Science and Engineering TCFurther Subject DidacticsWInformation