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A combinatorial algorithm for fault tolerant k-median clustering on a line metric

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dc.contributor.author Anderson, Nihesh
dc.contributor.author Arora, Kushagra
dc.contributor.author Raman, Rajiv (Advisor)
dc.contributor.author Das, Syamantak (Advisor)
dc.date.accessioned 2019-10-09T09:09:46Z
dc.date.available 2019-10-09T09:09:46Z
dc.date.issued 2019-04-15
dc.identifier.uri http://repository.iiitd.edu.in/xmlui/handle/123456789/781
dc.description.abstract Given a metric space X, a set of clients C X, and a set of facilities F X, such that X = F S C. the fault-tolerant k-median problem (FTM) requires to open k facilities in F so as to minimize the sum of distances from each client to r nearest open facilities. Fault-tolerant facility location (FTFL) allows the opening of a variable number of facilities, with an opening cost FTFL and FTM clustering are known NP-Hard problems, in any general metric space. Various approximation algorithms have been proposed to solve the problem in polynomial time. In this work, we consider the input space to be a line metric. M. Hajiaghayi et al. have proposed an LP-based technique to solve FTM in polynomial time. We propose the rst combinatorial algorithm to solve FTFL in polynomial time. This paper talks about the structure theorem that clearly de nes the structure of the underlying solution. The structure theorem is exploited to build a min-cost max ow model to solve FTFL on a line metric. The eventual goal is to nd a combinatorial polynomial-time solution to FTM on a line metric and extend it to tree metric space. Keywords : en_US
dc.language.iso en_US en_US
dc.publisher IIITD-Delhi en_US
dc.subject Facility Location en_US
dc.subject k-Median en_US
dc.subject Combinatorial Optimization en_US
dc.title A combinatorial algorithm for fault tolerant k-median clustering on a line metric en_US
dc.type Other en_US

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