Min sum clustering with penalties

Refael Hassin and Einat Or

European Journal of Operational Research, 2010, vol. 206, issue 3, 547-554

Abstract: Given a complete graph G=(V,E), a weight function on its edges, and a penalty function on its vertices, the penalized k-min-sum problem is the problem of finding a partition of V to k+1 sets, S1,...,Sk+1, minimizing , where for , and p(S)=[summation operator]i[set membership, variant]Spi. Our main result is a randomized approximation scheme for the metric version of the penalized 1-min-sum problem, when the ratio between the minimal and maximal penalty is bounded. For the metric penalized k-min-sum problem where k is a constant, we offer a 2-approximation.

Keywords: Min; sum; clustering; Outliers; Randomized; approximation; scheme (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:206:y:2010:i:3:p:547-554

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