Abstract
The problem of clustering a set of n points into k groups under various objective functions is studied. It is shown that under some objective functions clustering problems are NP-hard even when the points to be grouped are restricted to lie in the two dimensional euclidean space. Our results can be extended to show that their corresponding approximation problems are also NP-hard. It is shown that some restricted graph partition problems are also NP-hard.
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© 1982 Springer-Verlag
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Gonzalez, T.F. (1982). On the computational complexity of clustering and related problems. In: Drenick, R.F., Kozin, F. (eds) System Modeling and Optimization. Lecture Notes in Control and Information Sciences, vol 38. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0006133
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DOI: https://doi.org/10.1007/BFb0006133
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