Clustering with Penalty for Joint Occurrence of Objects: Computational Aspects

• URL: http://arxiv.org/abs/2102.01424v1
• Date: Tue, 2 Feb 2021 10:39:27 GMT
• Title: Clustering with Penalty for Joint Occurrence of Objects: Computational Aspects
• Authors: Ond\v{r}ej Sokol and Vladim\'ir Hol\'y
• Abstract summary: The method of Hol'y, Sokol and vCern'y clusters objects based on their incidence in a large number of given sets. The idea is to minimize the occurrence of multiple objects from the same cluster in the same set. In the current paper, we study computational aspects of the method.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The method of Hol\'y, Sokol and \v{C}ern\'y (Applied Soft Computing, 2017, Vol. 60, p. 752-762) clusters objects based on their incidence in a large number of given sets. The idea is to minimize the occurrence of multiple objects from the same cluster in the same set. In the current paper, we study computational aspects of the method. First, we prove that the problem of finding the optimal clustering is NP-hard. Second, to numerically find a suitable clustering, we propose to use the genetic algorithm augmented by a renumbering procedure, a fast task-specific local search heuristic and an initial solution based on a simplified model. Third, in a simulation study, we demonstrate that our improvements of the standard genetic algorithm significantly enhance its computational performance.

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