NP-Hardness of Some Euclidean Problems of Partitioning a Finite Set of Points
Problems of partitioning a finite set of Euclidean points (vectors) into clusters are considered. The criterion is to minimize the sum, over all clusters, of (1) squared norms of the sums of cluster elements normalized by the cardinality, (2) squared norms of the sums of cluster elements, and (3) no...
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Veröffentlicht in: | Computational mathematics and mathematical physics 2018-05, Vol.58 (5), p.822-826 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Problems of partitioning a finite set of Euclidean points (vectors) into clusters are considered. The criterion is to minimize the sum, over all clusters, of (1) squared norms of the sums of cluster elements normalized by the cardinality, (2) squared norms of the sums of cluster elements, and (3) norms of the sum of cluster elements. It is proved that all these problems are strongly NP-hard if the number of clusters is a part of the input and are NP-hard in the ordinary sense if the number of clusters is not a part of the input (is fixed). Moreover, the problems are NP-hard even in the case of dimension 1 (on a line). |
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ISSN: | 0965-5425 1555-6662 |
DOI: | 10.1134/S0965542518050123 |