Abstract.
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 different problems, including network design problems, feedback vertex set problems, and facility location problems.
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Received: June 19, 2000 / Accepted: February 7, 2001¶Published online October 2, 2001
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Williamson, D. The primal-dual method for approximation algorithms. Math. Program. 91, 447–478 (2002). https://doi.org/10.1007/s101070100262
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DOI: https://doi.org/10.1007/s101070100262