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Approximability of Capacitated Network Design

Approximability of capacitated network design
Authors: Deeparnab Chakrabarty; Chandra Chekuri; Sanjeev Khanna; Nitish Korula;

Approximability of Capacitated Network Design

Abstract

In the {\em capacitated} survivable network design problem (Cap-SNDP), we are given an undirected multi-graph where each edge has a capacity and a cost. The goal is to find a minimum cost subset of edges that satisfies a given set of pairwise minimum-cut requirements. Unlike its classical special case of SNDP when all capacities are unit, the approximability of Cap-SNDP is not well understood; even in very restricted settings no known algorithm achieves a $o(m)$ approximation, where $m$ is the number of edges in the graph. In this paper, we obtain several new results and insights into the approximability of Cap-SNDP.

19 pages, 1 figure

Keywords

FOS: Computer and information sciences, Discrete Mathematics (cs.DM), network design, linear programming relaxations, Programming involving graphs or networks, Approximation algorithms, Computer Science - Data Structures and Algorithms, Deterministic network models in operations research, Data Structures and Algorithms (cs.DS), approximation algorithms, Computer Science - Discrete Mathematics

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    popularity
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    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
22
Top 10%
Top 10%
Top 10%
Green
bronze