Lectures on proof verification and approximation algorithms
著者
書誌事項
Lectures on proof verification and approximation algorithms
（Lecture notes in computer science, 1367）
Springer, c1998
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注記
Includes bibliographical references (p. [325]-334) and indexes
内容説明・目次
内容説明
During the last few years, we have seen quite spectacular progress in the area of approximation algorithms: for several fundamental optimization problems we now actually know matching upper and lower bounds for their approximability. This textbook-like tutorial is a coherent and essentially self-contained presentation of the enormous recent progress facilitated by the interplay between the theory of probabilistically checkable proofs and aproximation algorithms. The basic concepts, methods, and results are presented in a unified way to provide a smooth introduction for newcomers. These lectures are particularly useful for advanced courses or reading groups on the topic.
目次
to the theory of complexity and approximation algorithms.- to randomized algorithms.- Derandomization.- Proof checking and non-approximability.- Proving the PCP-Theorem.- Parallel repetition of MIP(2,1) systems.- Bounds for approximating MaxLinEq3-2 and MaxEkSat.- Deriving non-approximability results by reductions.- Optimal non-approximability of MaxClique.- The hardness of approximating set cover.- Semidefinite programming and its applications to approximation algorithms.- Dense instances of hard optimization problems.- Polynomial time approximation schemes for geometric optimization problems in euclidean metric spaces.
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