Mixed integer linear programming formulation for K-means clustering problem

Kolos Cs. Ágoston () and Marianna E.-Nagy ()
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Kolos Cs. Ágoston: Corvinus University of Budapest
Marianna E.-Nagy: Corvinus University of Budapest
Authors registered in the RePEc Author Service: Marianna Eisenberg-Nagy

Central European Journal of Operations Research, 2024, vol. 32, issue 1, No 2, 27 pages

Abstract: Abstract The minimum sum-of-squares clusering is the most widely used clustering method. The minimum sum-of-squares clustering is usually solved by the heuristic KMEANS algorithm, which converges to a local optimum. A lot of effort has been made to solve such kind of problems, but a mixed integer linear programming formulation (MILP) is still missing. In this paper, we formulate MILP models. The advantage of MILP formulation is that users can extend the original problem with arbitrary linear constraints. We also present numerical results, we solve these models up to sample size of 150.

Keywords: Mathematical programming; Linear programming formulation; Clustering; K-means (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10100-023-00881-1

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