Work

Mixed integer linear programming formulation for K-means clustering problem

Year: 2023

Type: article

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.

Source: Central European Journal of Operations Research

DOI: 10.1007/s10100-023-00881-1

Authors: Kolos Cs. Ágoston, Marianna E.-Nagy

Institution: Corvinus University of Budapest

Language: English

Topic: Advanced Clustering Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,890

Funder: Budapesti Corvinus Egyetem