Exact and heuristic algorithms for the maximum weighted submatrix coverage problem

Markus Sinnl

European Journal of Operational Research, 2022, vol. 298, issue 3, 821-833

Abstract: The maximum weighted submatrix coverage problem is a recently introduced problem with applications in data mining. It is concerned with selecting K submatrices of a given numerical matrix such that the sum of the matrix-entries, which occur in at least one of the selected submatrices, is maximized. In the paper introducing the problem, a problem-specific constraint programming approach was developed and embedded in a large neighborhood-search to obtain a heuristic. A compact integer linear programming formulation was also presented, but deemed inefficient due to its size.

Keywords: Combinatorial optimization; Data mining; Branch-and-cut; Benders decomposition; Local search (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:298:y:2022:i:3:p:821-833

DOI: 10.1016/j.ejor.2021.07.035

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