Approximation Algorithms Via Randomized Rounding: A Survey (1999)
| Venue: | Series in Advanced Topics in Mathematics, Polish Scientific Publishers PWN |
| Citations: | 14 - 2 self |
BibTeX
@INPROCEEDINGS{Srinivasan99approximationalgorithms,
author = {Aravind Srinivasan},
title = {Approximation Algorithms Via Randomized Rounding: A Survey},
booktitle = {Series in Advanced Topics in Mathematics, Polish Scientific Publishers PWN},
year = {1999},
pages = {9--71},
publisher = {Publishers}
}
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Abstract
Approximation algorithms provide a natural way to approach computationally hard problems. There are currently many known paradigms in this area, including greedy algorithms, primal-dual methods, methods based on mathematical programming (linear and semidefinite programming in particular), local improvement, and "low distortion" embeddings of general metric spaces into special families of metric spaces. Randomization is a useful ingredient in many of these approaches, and particularly so in the form of randomized rounding of a suitable relaxation of a given problem. We survey this technique here, with a focus on correlation inequalities and their applications.
