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SODA
2008
ACM

Adaptive local ratio

8 years 11 months ago
Adaptive local ratio
Local ratio is a well-known paradigm for designing approximation algorithms for combinatorial optimization problems. At a very high level, a local-ratio algorithm first decomposes the input weight function w into a positive linear combination of simpler weight functions or models. Guided by this process, a solution S is constructed such that S is -approximate with respect to each model used in the decomposition. As a result, S is -approximate under w as well. These models usually have a very simple structure that remains "unchanged" throughout the execution of the algorithm. In this work we show that adaptively choosing a model from a richer spectrum of functions can lead to a better local ratio. Indeed, by turning the search for a good model into an optimization problem of its own, we get improved approximations for a data migration problem. Key words. local-ratio technique, primal-dual schema, approximation algorithms, scheduling problems AMS subject classifications. 90C05,...
Julián Mestre
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2008
Where SODA
Authors Julián Mestre
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