Journal of Nonlinear and Variational Analysis

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DOI: 10.23952/jnva.8.2024.6.09

Volume 8, Issue 6, 1 December 2024, Pages 987-1012

 

Abstract. In this paper, we consider a planar clustering problem with location constraints for cluster centers. A simple adaptation of the k-means algorithm solving the presented problem to local optimality is outlined. We further show that our problem can be stated as a MIQCP (mixed-integer-quadratically-constrained-programming) problem, and some results to solve the formulated problem to global optimality with a popular solver are presented. We also present a specialized enumeration algorithm which can be used to find the global optima of the problem and our numerical experiments indicate that this approach is a better choice in comparison to solving the formulated MIQCP problem with a general solver.

 

How to Cite this Article:
M. Kepalas, J. Žilinskas, Solving net-constrained clustering problem, J. Nonlinear Var. Anal. 8 (2024), 987-1012.