Time: Tue/Thu 10:20-11:40
Location: TTIC conference room 530.
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Course description:Many combinatorial optimization problems are NP-hard, and are therefore unlikely to have efficient algorithms. However, these problems still need to be handled in practice. A natural approach to overcome this difficulty is to settle for approximation algorithms: efficient algorithms that are guaranteed to produce near-optimal solutions. The main focus of this course is on the design of approximation algorithms for combinatorial optimization problems. While exploring algorithms for central combinatorial optimization problems, we will also focus on major approaches and techniques in algorithm design, such as LP-rounding, Primal-Dual schema, metric methods, SDP rounding and so on. We will also address the question why some problems have good approximation algorithms while other do not, via hardness of approximation, or inapproximability, proofs.
Tentative list of topics: