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,...

• Type: Conference
• Year: 2008
• Where: SODA
• Authors: Julián Mestre
• Keywords: Algorithms, Approximation Algorithms, Local Ratio, Optimization Problem, SODA 2008