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 meth...

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Bibliographic Details
Published in:Mathematical programming 2002-02, Vol.91 (3), p.447-478
Main Author: WILLIAMSON, David P
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Approximation
Assignment problem
Exact sciences and technology
Flows in networks. Combinatorial problems
Guarantees
Heuristic
Integer programming
Linear programming
Operational research and scientific management
Operational research. Management science
Optimization
Research centers
Traveling salesman problem
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Summary: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.
ISSN:0025-5610
1436-4646
DOI:10.1007/s101070100262