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.
This book coherently summarizes the spectacular progress achieved in the areas of approximation algorithms and combinatorial optimization during the last few years. Includes supplementary material: sn.pub/extras
Ernst W. Mayr
algorithm algorithms approximation algorithms complexity complexity theory optimization programming proof verification randomized computation verification algorithm analysis and problem complexity combinatorics