The Primal-Dual Method for Approximation Algorithms

In this survey, we give an overview of a technique used to design and analyze algorithms that provide approximate solutions to NP -hard problems in combinatorial optimization. Because of parallels with the primal-dual method commonly used in combinatorial optimization, we call it the primal-dual method for approximation algorithms. We show how this technique can be used to derive approximation algorithms for a number of di#erent problems, including network design problems, feedback vertex set problems, and facility location problems