Divide-and-conquer approximation algorithms via spreading metrics

Guy Even*, Joseph Naor, Satish Rao, Baruch Schieber

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

A novel divide-and-conquer paradigm for approximating NP-hard graph optimization problems is presented. The paradigm models graph optimization problems that satisfy two properties. First, a divide-and-conquer approach is applicable. Second, a fractional spreading metric is computable in polynomial time. The spreading metric assigns fractional lengths to either edges or vertices of the input graph, such that all subgraphs on which the optimization problem is non-trivial have large diameters. In addition, the spreading metric provides a lower bound on the cost of solving the optimization problem.

Original languageEnglish
Pages (from-to)62-71
Number of pages10
JournalAnnual Symposium on Foundations of Computer Science - Proceedings
StatePublished - 1995
Externally publishedYes
EventProceedings of the 1995 IEEE 36th Annual Symposium on Foundations of Computer Science - Milwaukee, WI, USA
Duration: 23 Oct 199525 Oct 1995

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