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. With: 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)