Synthetic dataset used in "The maximum weighted submatrix coverage problem: A CP approach"
Synthetic dataset used in "The maximum weighted submatrix coverage problem: A CP approach".
Includes both the generated datasets as a zip archive and the python script used to generate them.
Each instance is composed of two files in the form
XxY_K_O_0xN_AxB_Smatrix.tsv being the matrix to use. Each row on a separate line, with tab-separated cells.
XxY_K_O_0xN_AxB_Ssolution.txt giving the implanted solution. One submatrix per line. Then two JSON arrays follow, separated by a tabulation. The first is the list of rows selected in the submatrix, the second the columns.
X and Y the size of the matrix
K the number of submatrices in the implanted solution
O the (minimum) overlap percentage of each submatrix
N the sigma used for the background noise
A and B the size of the implanted submatrices (subject to noise)